Index A | B | C | D | E | F | G | H | I | J | K | L | M | N | O | P | R | S | T | U | V | W | X | Y | Z A acceptance_rate (pymixef.pharmacometrics.estimation.SAEMResult attribute) (pymixef.pharmacometrics.SAEMResult attribute) accepted (pymixef.pharmacometrics.estimation.SAEMResult attribute) (pymixef.pharmacometrics.SAEMResult attribute) action (pymixef.data.AuditRecord attribute) (pymixef.pharmacometrics.AuditEntry attribute) (pymixef.pharmacometrics.events.AuditEntry attribute) adapt() (pymixef.data.DataAdapter static method) adapt_data() (in module pymixef.data) additional (pymixef.pharmacometrics.CanonicalEvent attribute) (pymixef.pharmacometrics.events.CanonicalEvent attribute) additive() (in module pymixef.pharmacometrics) (in module pymixef.pharmacometrics.pk) additive_sigma (pymixef.pharmacometrics.CombinedError attribute) (pymixef.pharmacometrics.pk.CombinedError attribute) AdditiveError (class in pymixef.pharmacometrics) (class in pymixef.pharmacometrics.pk) ADDL (pymixef.pharmacometrics.CanonicalEvent property) addl (pymixef.pharmacometrics.CanonicalEvent property) ADDL (pymixef.pharmacometrics.events.CanonicalEvent property) addl (pymixef.pharmacometrics.events.CanonicalEvent property) adjusted_rows (pymixef.data.PatternMixtureResult property) (pymixef.PatternMixtureResult property) after (pymixef.data.PatternMixtureRecord attribute) (pymixef.ir.DiffEntry attribute) after_hash (pymixef.ir.ModelDiff attribute) aliased_fixed (pymixef.formula.FormulaExplanation attribute) alpha (pymixef.pharmacometrics.pk.TwoCompartmentRates attribute) (pymixef.pharmacometrics.TwoCompartmentRates attribute) amount (pymixef.pharmacometrics.CanonicalEvent attribute) (pymixef.pharmacometrics.Dose attribute) (pymixef.pharmacometrics.dsl.Dose attribute) (pymixef.pharmacometrics.events.CanonicalEvent attribute) amount_status (pymixef.pharmacometrics.CanonicalEvent attribute) (pymixef.pharmacometrics.events.CanonicalEvent attribute) AMT (pymixef.pharmacometrics.CanonicalEvent property) amt (pymixef.pharmacometrics.CanonicalEvent property) AMT (pymixef.pharmacometrics.events.CanonicalEvent property) amt (pymixef.pharmacometrics.events.CanonicalEvent property) Analysis row analysis_fingerprint (pymixef.data.DataAudit attribute) analysis_rows (pymixef.data.DataAudit attribute) annotations (pymixef.ir.IRNode attribute) AnteDependence (class in pymixef.covariance) AnteDependenceCovariance (in module pymixef.covariance) apply_random_effects() (in module pymixef.pharmacometrics) (in module pymixef.pharmacometrics.estimation) Approximation approximation_sensitivity() (in module pymixef) (in module pymixef.compare) ApproximationSensitivityResult (class in pymixef) (class in pymixef.compare) AR1 (class in pymixef.covariance) AR1Covariance (in module pymixef.covariance) arguments (pymixef.pharmacometrics.dsl.Expr attribute) (pymixef.pharmacometrics.Expr attribute) as_expr() (in module pymixef.pharmacometrics) (in module pymixef.pharmacometrics.dsl) (pymixef.pharmacometrics.dsl.Eta method) (pymixef.pharmacometrics.dsl.Param method) (pymixef.pharmacometrics.dsl.State method) (pymixef.pharmacometrics.dsl.Symbol method) (pymixef.pharmacometrics.Eta method) (pymixef.pharmacometrics.Param method) (pymixef.pharmacometrics.State method) (pymixef.pharmacometrics.Symbol method) assert_within() (pymixef.compare.ComparisonResult method) (pymixef.ComparisonResult method) assess() (pymixef.convergence.ConvergenceReport class method) (pymixef.ConvergenceReport class method) atol (pymixef.pharmacometrics.ode.ODESolverMetadata attribute) (pymixef.pharmacometrics.ODESolverMetadata attribute) audit (pymixef.data.AuditedData attribute) (pymixef.formula.DesignMatrices attribute) (pymixef.pharmacometrics.events.EventTable attribute) (pymixef.pharmacometrics.EventTable attribute) audit_data() (in module pymixef.data) AuditedData (class in pymixef.data) AuditEntry (class in pymixef.pharmacometrics) (class in pymixef.pharmacometrics.events) AuditRecord (class in pymixef.data) authoring_mode (pymixef.pharmacometrics.CompiledModel attribute) (pymixef.pharmacometrics.dsl.CompiledModel attribute) B Backend (class in pymixef.backends) (class in pymixef.backends.base) backend_mapping() (in module pymixef.backends.base) BackendError, [1] BackendInputError, [1] BackendNumericalError, [1] BackendUnsupportedError, [1] baseline (pymixef.ApproximationSensitivityResult attribute) (pymixef.compare.ApproximationSensitivityResult attribute) before (pymixef.data.PatternMixtureRecord attribute) (pymixef.ir.DiffEntry attribute) before_hash (pymixef.ir.ModelDiff attribute) Bernoulli (class in pymixef.families) Beta (class in pymixef.families) beta (pymixef.pharmacometrics.pk.TwoCompartmentRates attribute) (pymixef.pharmacometrics.TwoCompartmentRates attribute) Binomial (class in pymixef.families) bioavailability (pymixef.pharmacometrics.CanonicalEvent attribute) (pymixef.pharmacometrics.Dose attribute) (pymixef.pharmacometrics.dsl.Dose attribute) (pymixef.pharmacometrics.events.CanonicalEvent attribute) BITWISE (pymixef.ReproducibilityClass attribute) block (pymixef.backends.base.CovarianceParameterization attribute) (pymixef.pharmacometrics.dsl.Eta attribute) (pymixef.pharmacometrics.Eta attribute) bootstrap() (in module pymixef) (in module pymixef.inference) BootstrapResult (class in pymixef) (class in pymixef.inference) boundaries (pymixef.convergence.ConvergenceReport attribute) (pymixef.ConvergenceReport attribute) boundary (pymixef.BoundaryRecord attribute) (pymixef.convergence.BoundaryRecord attribute) Boundary estimate BoundaryRecord (class in pymixef) (class in pymixef.convergence) bounded() (pymixef.pharmacometrics.dsl.Param class method) (pymixef.pharmacometrics.Param class method) BoundedTransform (class in pymixef.transforms) bounds (pymixef.ir.ParameterIR attribute) burn_in (pymixef.pharmacometrics.estimation.SAEMControl attribute) (pymixef.pharmacometrics.estimation.SAEMResult attribute) (pymixef.pharmacometrics.SAEMControl attribute) (pymixef.pharmacometrics.SAEMResult attribute) by_status() (pymixef.interoperability.base.CompatibilityReport method) (pymixef.interoperability.CompatibilityReport method) C Canonical event canonical_json() (pymixef.ir.ModelIR method) (pymixef.ModelIR method) CanonicalEvent (class in pymixef.pharmacometrics) (class in pymixef.pharmacometrics.events) canonicalize_events() (in module pymixef.pharmacometrics) (in module pymixef.pharmacometrics.events) Capability (class in pymixef.capabilities) capability (pymixef.validation.TraceabilityRecord attribute) capture() (pymixef.provenance.RunManifest class method) (pymixef.RunManifest class method) categorical (pymixef.data.ColumnSchema attribute) categories (pymixef.ir.ModelDiff property) category (pymixef.ir.DiffEntry attribute) cauchit (pymixef.families.links attribute) cdf() (pymixef.families.Bernoulli method) (pymixef.families.Beta method) (pymixef.families.Binomial method) (pymixef.families.Censored method) (pymixef.families.COMPoisson method) (pymixef.families.Exponential method) (pymixef.families.Family method) (pymixef.families.Gamma method) (pymixef.families.Gaussian method) (pymixef.families.GeneralizedPoisson method) (pymixef.families.Gompertz method) (pymixef.families.Hurdle method) (pymixef.families.InverseGaussian method) (pymixef.families.LogLogistic method) (pymixef.families.LogNormal method) (pymixef.families.LogNormalSurvival method) (pymixef.families.Multinomial method) (pymixef.families.NegativeBinomial2 method) (pymixef.families.Ordinal method) (pymixef.families.PiecewiseExponential method) (pymixef.families.Poisson method) (pymixef.families.StudentT method) (pymixef.families.Truncated method) (pymixef.families.Tweedie method) (pymixef.families.Weibull method) (pymixef.families.ZeroInflated method) Censored (class in pymixef.families) censored (pymixef.pharmacometrics.ConditionalObjective attribute) (pymixef.pharmacometrics.estimation.ConditionalObjective attribute) censored_above (pymixef.pharmacometrics.dsl.Observation attribute) (pymixef.pharmacometrics.Observation attribute) censored_below (pymixef.pharmacometrics.dsl.Observation attribute) (pymixef.pharmacometrics.Observation attribute) CENSORED_RESPONSE (pymixef.data.MissingnessKind attribute) CensoredFamily (in module pymixef.families) central (pymixef.pharmacometrics.ode.SensitivityCheck attribute) (pymixef.pharmacometrics.SensitivityCheck attribute) central_volume (pymixef.pharmacometrics.pk.TwoCompartmentPK attribute) (pymixef.pharmacometrics.TwoCompartmentPK attribute) change (pymixef.ir.DiffEntry attribute) change_impact() (in module pymixef) (in module pymixef.validation) cho_solve() (in module pymixef.backends.base) CholeskyCovarianceTransform (class in pymixef.transforms) classify_change() (in module pymixef.validation) clearance (pymixef.pharmacometrics.OneCompartmentPK attribute) (pymixef.pharmacometrics.pk.OneCompartmentPK attribute) (pymixef.pharmacometrics.pk.TwoCompartmentPK attribute) (pymixef.pharmacometrics.TwoCompartmentPK attribute) cloglog (pymixef.families.links attribute) CMT (pymixef.pharmacometrics.CanonicalEvent property) cmt (pymixef.pharmacometrics.CanonicalEvent property) CMT (pymixef.pharmacometrics.events.CanonicalEvent property) cmt (pymixef.pharmacometrics.events.CanonicalEvent property) code (pymixef.model.ValidationFinding attribute) (pymixef.pharmacometrics.AuditEntry attribute) (pymixef.pharmacometrics.ConditionalModeError attribute) (pymixef.pharmacometrics.dsl.DSLValidationError attribute) (pymixef.pharmacometrics.dsl.ValidationMessage attribute) (pymixef.pharmacometrics.DSLValidationError attribute) (pymixef.pharmacometrics.estimation.ConditionalModeError attribute) (pymixef.pharmacometrics.estimation.EstimationError attribute) (pymixef.pharmacometrics.estimation.SAEMError attribute) (pymixef.pharmacometrics.estimation.UnsupportedEstimatorError attribute) (pymixef.pharmacometrics.EstimationError attribute) (pymixef.pharmacometrics.events.AuditEntry attribute) (pymixef.pharmacometrics.events.EventValidationError attribute) (pymixef.pharmacometrics.EventValidationError attribute) (pymixef.pharmacometrics.ode.ODESimulationError attribute) (pymixef.pharmacometrics.ode.UnsupportedEventSemantics attribute) (pymixef.pharmacometrics.ODESimulationError attribute) (pymixef.pharmacometrics.pk.PKValidationError attribute) (pymixef.pharmacometrics.PKValidationError attribute) (pymixef.pharmacometrics.SAEMError attribute) (pymixef.pharmacometrics.UnsupportedEstimatorError attribute) (pymixef.pharmacometrics.UnsupportedEventSemantics attribute) (pymixef.pharmacometrics.ValidationMessage attribute) (pymixef.WarningRecord attribute) (pymixef.warnings.PyMixEFWarning property) coefficient_count (pymixef.backends.base.RandomBlockData property) coefficient_labels() (pymixef.backends.base.RandomBlockData method) column_names (pymixef.data.ColumnarData property) ColumnarData (class in pymixef.data) columns (pymixef.data.AuditRecord attribute) (pymixef.data.ColumnarData attribute) (pymixef.diagnostics.DiagnosticTable attribute) (pymixef.ir.FixedEffectIR attribute) ColumnSchema (class in pymixef.data) combined() (in module pymixef.pharmacometrics) (in module pymixef.pharmacometrics.pk) CombinedError (class in pymixef.pharmacometrics) (class in pymixef.pharmacometrics.pk) compare() (in module pymixef.compare) ComparisonResult (class in pymixef) (class in pymixef.compare) compartment (pymixef.pharmacometrics.CanonicalEvent attribute) (pymixef.pharmacometrics.Dose attribute) (pymixef.pharmacometrics.dsl.Dose attribute) (pymixef.pharmacometrics.events.CanonicalEvent attribute) compatibility (pymixef.compare.ComparisonResult attribute) (pymixef.ComparisonResult attribute) CompatibilityError, [1] CompatibilityReport (class in pymixef.interoperability) (class in pymixef.interoperability.base) compatible_engines (pymixef.model.ValidationReport attribute) compile() (pymixef.Model method) (pymixef.model.Model method) (pymixef.pharmacometrics.dsl.ModelDefinition method) (pymixef.pharmacometrics.ModelDefinition method) compile_formula() (in module pymixef.formula) compiled_model() (in module pymixef.pharmacometrics) (in module pymixef.pharmacometrics.dsl) CompiledData (class in pymixef.backends.base) CompiledModel (class in pymixef.pharmacometrics) (class in pymixef.pharmacometrics.dsl) COMPoisson (class in pymixef.families) component (pymixef.ir.LikelihoodIR attribute) (pymixef.model.ValidationFinding attribute) (pymixef.WarningRecord attribute) components() (pymixef.pharmacometrics.ConditionalObjective method) (pymixef.pharmacometrics.estimation.ConditionalObjective method) CompoundSymmetry (class in pymixef.covariance) CompoundSymmetryCovariance (in module pymixef.covariance) condition_number (pymixef.convergence.HessianDiagnostics attribute) (pymixef.HessianDiagnostics attribute) Conditional mode Conditional prediction conditional_mode_failures (pymixef.convergence.ConvergenceReport attribute) (pymixef.ConvergenceReport attribute) conditional_mode_objective() (in module pymixef.pharmacometrics) (in module pymixef.pharmacometrics.estimation) ConditionalModeError, [1] ConditionalModeResult (class in pymixef.pharmacometrics) (class in pymixef.pharmacometrics.estimation) ConditionalObjective (class in pymixef.pharmacometrics) (class in pymixef.pharmacometrics.estimation) constraint (pymixef.pharmacometrics.dsl.Param attribute) (pymixef.pharmacometrics.Param attribute) contrast_coding (pymixef.data.DataAudit attribute) (pymixef.formula.DesignMatrices attribute) (pymixef.formula.FormulaExplanation attribute) contrasts() (in module pymixef.backends.mmrm) conventions (pymixef.compare.ComparisonResult attribute) (pymixef.ComparisonResult attribute) convergence (pymixef.FitResult attribute) (pymixef.provenance.RunManifest attribute) (pymixef.results.FitResult attribute) (pymixef.RunManifest attribute) convergence_mapping() (in module pymixef.backends.base) ConvergenceReport (class in pymixef) (class in pymixef.convergence) ConwayMaxwellPoisson (in module pymixef.families) core_version() (in module pymixef.native) correlated (pymixef.backends.base.RandomBlockData attribute) (pymixef.formula.RandomDesignBlock attribute) (pymixef.formula.RandomTerm attribute) (pymixef.ir.RandomEffectIR attribute) (pymixef.model.Random attribute) (pymixef.Random attribute) correlated() (pymixef.pharmacometrics.dsl.Eta class method) (pymixef.pharmacometrics.Eta class method) covariance (pymixef.ir.RandomEffectIR attribute) (pymixef.model.Random attribute) (pymixef.pharmacometrics.ConditionalModeResult attribute) (pymixef.pharmacometrics.dsl.Eta attribute) (pymixef.pharmacometrics.estimation.ConditionalModeResult attribute) (pymixef.pharmacometrics.Eta attribute) (pymixef.Random attribute) Covariance axis covariance() (pymixef.covariance.AnteDependence method) (pymixef.covariance.AR1 method) (pymixef.covariance.CompoundSymmetry method) (pymixef.covariance.CovarianceStructure method) (pymixef.covariance.Diagonal method) (pymixef.covariance.HeterogeneousAR1 method) (pymixef.covariance.HeterogeneousToeplitz method) (pymixef.covariance.KnownCovariance method) (pymixef.covariance.SpatialPower method) (pymixef.covariance.Toeplitz method) (pymixef.covariance.Unstructured method) (pymixef.plugins.CovariancePlugin method) covariance_from_hessian() (in module pymixef.backends.base) covariance_singularity_table() (in module pymixef.diagnostics) covariance_slices() (in module pymixef.backends.base) covariance_structure() (in module pymixef.covariance) covariance_structures (pymixef.ir.ModelIR attribute) (pymixef.ModelIR attribute) CovarianceError, [1] CovarianceIR (class in pymixef.ir) CovarianceParameterization (class in pymixef.backends.base) CovariancePlugin (class in pymixef.plugins) CovarianceStructure (class in pymixef.covariance) CovarianceValidation (class in pymixef.covariance) CovarianceWarning COVARIATE (pymixef.pharmacometrics.events.EventType attribute) (pymixef.pharmacometrics.EventType attribute) covariate() (in module pymixef.pharmacometrics) (in module pymixef.pharmacometrics.dsl) covariates (pymixef.pharmacometrics.CanonicalEvent attribute) (pymixef.pharmacometrics.events.CanonicalEvent attribute) (pymixef.pharmacometrics.ode.ODEContext attribute) (pymixef.pharmacometrics.ODEContext attribute) create_validation_bundle() (in module pymixef) (in module pymixef.validation) created_at_utc (pymixef.provenance.RunManifest attribute) (pymixef.RunManifest attribute) D d() (in module pymixef.pharmacometrics) (in module pymixef.pharmacometrics.dsl) data (pymixef.data.AuditedData attribute) (pymixef.data.PatternMixtureResult attribute) (pymixef.PatternMixtureResult attribute) Data audit data_hash (pymixef.provenance.RunManifest attribute) (pymixef.RunManifest attribute) data_schema (pymixef.ir.ModelIR attribute) (pymixef.ModelIR attribute) DataAdapter (class in pymixef.data) DataAudit (class in pymixef.data) DataAuditWarning DataError, [1] declaration_signature (pymixef.pharmacometrics.dsl.ModelDefinition property) (pymixef.pharmacometrics.ModelDefinition property) default_code (pymixef.CompatibilityError attribute) (pymixef.CovarianceError attribute) (pymixef.DataError attribute) (pymixef.errors.CompatibilityError attribute) (pymixef.errors.CovarianceError attribute) (pymixef.errors.DataError attribute) (pymixef.errors.FormulaError attribute) (pymixef.errors.IRValidationError attribute) (pymixef.errors.IRVersionError attribute) (pymixef.errors.PluginError attribute) (pymixef.errors.PyMixEFError attribute) (pymixef.errors.TransformError attribute) (pymixef.errors.UnsupportedCapabilityError attribute) (pymixef.errors.ValidationError attribute) (pymixef.FormulaError attribute) (pymixef.IRValidationError attribute) (pymixef.IRVersionError attribute) (pymixef.PluginError attribute) (pymixef.PyMixEFError attribute) (pymixef.UnsupportedCapabilityError attribute) (pymixef.ValidationError attribute) default_link (pymixef.families.Bernoulli attribute) (pymixef.families.Beta attribute) (pymixef.families.Binomial attribute) (pymixef.families.COMPoisson attribute) (pymixef.families.Exponential attribute) (pymixef.families.Family attribute) (pymixef.families.Gamma attribute) (pymixef.families.Gaussian attribute) (pymixef.families.GeneralizedPoisson attribute) (pymixef.families.Gompertz attribute) (pymixef.families.InverseGaussian attribute) (pymixef.families.LogLogistic attribute) (pymixef.families.LogNormal attribute) (pymixef.families.LogNormalSurvival attribute) (pymixef.families.Multinomial attribute) (pymixef.families.NegativeBinomial2 attribute) (pymixef.families.Ordinal attribute) (pymixef.families.PiecewiseExponential attribute) (pymixef.families.Poisson attribute) (pymixef.families.StudentT attribute) (pymixef.families.Tweedie attribute) (pymixef.families.Weibull attribute) Degrees of freedom (DF) delta (pymixef.data.PatternMixtureRecord attribute) DenseLMMBackend (in module pymixef.backends) (in module pymixef.backends.lmm) dependencies (pymixef.ir.IRNode attribute) derivative() (in module pymixef.pharmacometrics) (in module pymixef.pharmacometrics.dsl) (pymixef.families.Link method) (pymixef.pharmacometrics.dsl.State method) (pymixef.pharmacometrics.State method) derivatives() (pymixef.covariance.CovarianceStructure method) description (pymixef.pharmacometrics.dsl.Param attribute) (pymixef.pharmacometrics.Param attribute) design (pymixef.backends.base.RandomBlockData attribute) DesignMatrices (class in pymixef.formula) details (pymixef.data.AuditRecord attribute) (pymixef.pharmacometrics.AuditEntry attribute) (pymixef.pharmacometrics.events.AuditEntry attribute) (pymixef.WarningRecord attribute) DETERMINISTIC_TOLERANCE (pymixef.ReproducibilityClass attribute) diagnostic() (pymixef.FitResult method) (pymixef.results.FitResult method) diagnostic_data (pymixef.FitResult attribute) (pymixef.results.FitResult attribute) DiagnosticTable (class in pymixef.diagnostics) Diagonal (class in pymixef.covariance) DiagonalCovariance (in module pymixef.covariance) diff() (pymixef.ir.ModelIR method) (pymixef.ModelIR method) diff_models() (in module pymixef) (in module pymixef.ir) DiffEntry (class in pymixef.ir) differentiability (pymixef.ir.IRNode attribute) DifferentialEquation (class in pymixef.pharmacometrics) (class in pymixef.pharmacometrics.dsl) dimension (pymixef.covariance.CovarianceValidation attribute) (pymixef.ir.CovarianceIR attribute) (pymixef.transforms.CholeskyCovarianceTransform attribute) dimensions (pymixef.ir.IRNode attribute) (pymixef.pharmacometrics.dsl.ModelValidation attribute) (pymixef.pharmacometrics.ModelValidation attribute) discover_plugins() (in module pymixef.plugins) discrete (pymixef.families.Bernoulli attribute) (pymixef.families.Binomial attribute) (pymixef.families.COMPoisson attribute) (pymixef.families.Family attribute) (pymixef.families.GeneralizedPoisson attribute) (pymixef.families.Multinomial attribute) (pymixef.families.NegativeBinomial2 attribute) (pymixef.families.Ordinal attribute) (pymixef.families.Poisson attribute) dispersion (pymixef.Model attribute) (pymixef.model.Model attribute) distribution (pymixef.ir.PriorIR attribute) Dose (class in pymixef.pharmacometrics) (class in pymixef.pharmacometrics.dsl) DOSE (pymixef.pharmacometrics.events.EventType attribute) (pymixef.pharmacometrics.EventType attribute) DoseAmountStatus (class in pymixef.pharmacometrics) (class in pymixef.pharmacometrics.events) doses (pymixef.pharmacometrics.CompiledModel attribute) (pymixef.pharmacometrics.dsl.CompiledModel attribute) draws (pymixef.BootstrapResult attribute) (pymixef.inference.BootstrapResult attribute) dry_run() (in module pymixef.formula) DSLValidationError, [1] dtype (pymixef.data.ColumnSchema attribute) DUR (pymixef.pharmacometrics.CanonicalEvent property) (pymixef.pharmacometrics.events.CanonicalEvent property) duration (pymixef.pharmacometrics.CanonicalEvent attribute) (pymixef.pharmacometrics.Dose attribute) (pymixef.pharmacometrics.dsl.Dose attribute) (pymixef.pharmacometrics.events.CanonicalEvent attribute) dv (pymixef.pharmacometrics.CanonicalEvent attribute) DV (pymixef.pharmacometrics.CanonicalEvent property) dv (pymixef.pharmacometrics.events.CanonicalEvent attribute) DV (pymixef.pharmacometrics.events.CanonicalEvent property) dv (pymixef.pharmacometrics.EventSnapshot attribute) (pymixef.pharmacometrics.ode.EventSnapshot attribute) E effective_amount (pymixef.pharmacometrics.CanonicalEvent property) (pymixef.pharmacometrics.events.CanonicalEvent property) effective_rank (pymixef.convergence.HessianDiagnostics attribute) (pymixef.covariance.CovarianceValidation attribute) (pymixef.HessianDiagnostics attribute) effective_rate (pymixef.pharmacometrics.CanonicalEvent property) (pymixef.pharmacometrics.events.CanonicalEvent property) eigenvalue_ratio (pymixef.covariance.CovarianceValidation attribute) eigenvalues (pymixef.covariance.CovarianceValidation attribute) elapsed_seconds (pymixef.provenance.RunManifest attribute) (pymixef.RunManifest attribute) emit_warning() (in module pymixef.warnings) endpoint (pymixef.pharmacometrics.dsl.Observation attribute) (pymixef.pharmacometrics.Observation attribute) Engine engine (pymixef.ExecutionPlan attribute) (pymixef.FitResult attribute) (pymixef.model.ExecutionPlan attribute) (pymixef.model.ValidationReport attribute) (pymixef.provenance.RunManifest attribute) (pymixef.results.FitResult attribute) (pymixef.RunManifest attribute) engine_metrics (pymixef.convergence.ConvergenceReport attribute) (pymixef.ConvergenceReport attribute) EngineCompatibilityError, [1] entries (pymixef.ir.ModelDiff attribute) environment (pymixef.provenance.RunManifest attribute) (pymixef.RunManifest attribute) environment_snapshot() (in module pymixef.provenance) equal (pymixef.ir.ModelDiff property) equation_kind (pymixef.ir.StateEquationIR attribute) equations (pymixef.pharmacometrics.CompiledModel attribute) (pymixef.pharmacometrics.dsl.CompiledModel attribute) error (pymixef.pharmacometrics.ConditionalObjective attribute) (pymixef.pharmacometrics.dsl.Observation attribute) (pymixef.pharmacometrics.estimation.ConditionalObjective attribute) (pymixef.pharmacometrics.Observation attribute) error_parameters (pymixef.pharmacometrics.ConditionalObjective attribute) (pymixef.pharmacometrics.estimation.ConditionalObjective attribute) Estimand estimated_marginal_means() (in module pymixef.backends.mmrm) EstimationError, [1] estimator (pymixef.ir.ModelIR attribute) (pymixef.ModelIR attribute) estimator_compatibility (pymixef.pharmacometrics.dsl.ModelValidation attribute) (pymixef.pharmacometrics.ModelValidation attribute) EstimatorPlugin (class in pymixef.plugins) Eta (class in pymixef.pharmacometrics) (class in pymixef.pharmacometrics.dsl) eta (pymixef.pharmacometrics.ConditionalModeResult attribute) (pymixef.pharmacometrics.estimation.ConditionalModeResult attribute) eta_dimension (pymixef.pharmacometrics.ConditionalObjective property) (pymixef.pharmacometrics.estimation.ConditionalObjective property) eta_shrinkage() (in module pymixef.pharmacometrics) (in module pymixef.pharmacometrics.estimation) etas (pymixef.pharmacometrics.CompiledModel attribute) (pymixef.pharmacometrics.dsl.CompiledModel attribute) evaluate() (pymixef.pharmacometrics.dsl.Expr method) (pymixef.pharmacometrics.Expr method) event_actions (pymixef.pharmacometrics.ode.ODESolverMetadata attribute) (pymixef.pharmacometrics.ODESolverMetadata attribute) event_type (pymixef.ir.EventIR attribute) (pymixef.pharmacometrics.CanonicalEvent property) (pymixef.pharmacometrics.events.CanonicalEvent property) EventIR (class in pymixef.ir) events (pymixef.ir.ModelIR attribute) (pymixef.ModelIR attribute) (pymixef.pharmacometrics.events.EventTable attribute) (pymixef.pharmacometrics.EventTable attribute) EventSnapshot (class in pymixef.pharmacometrics) (class in pymixef.pharmacometrics.ode) EventTable (class in pymixef.pharmacometrics) (class in pymixef.pharmacometrics.events) EventType (class in pymixef.pharmacometrics) (class in pymixef.pharmacometrics.events) EventValidationError, [1] evid (pymixef.pharmacometrics.CanonicalEvent attribute) EVID (pymixef.pharmacometrics.CanonicalEvent property) evid (pymixef.pharmacometrics.events.CanonicalEvent attribute) EVID (pymixef.pharmacometrics.events.CanonicalEvent property) evidence (pymixef.capabilities.Capability attribute) (pymixef.validation.TraceabilityRecord attribute) excluded_row_ids (pymixef.data.DataAudit property) excluded_rows (pymixef.data.DataAudit property) (pymixef.formula.FormulaExplanation attribute) ExecutionPlan (class in pymixef) (class in pymixef.model) exp() (in module pymixef.pharmacometrics) (in module pymixef.pharmacometrics.dsl) expand_additional() (pymixef.pharmacometrics.events.EventTable method) (pymixef.pharmacometrics.EventTable method) expand_infusions() (pymixef.pharmacometrics.events.EventTable method) (pymixef.pharmacometrics.EventTable method) expanded (pymixef.formula.RandomDesignBlock attribute) expanded_matrix() (pymixef.backends.base.CovarianceParameterization method) EXPERIMENTAL (pymixef.Maturity attribute) experimental (pymixef.pharmacometrics.estimation.SAEMResult attribute) (pymixef.pharmacometrics.SAEMResult attribute) experimental_saem() (in module pymixef.pharmacometrics) (in module pymixef.pharmacometrics.estimation) explain() (pymixef.ExecutionPlan method) (pymixef.formula.DesignMatrices method) (pymixef.formula.FormulaSpec method) (pymixef.Model method) (pymixef.model.ExecutionPlan method) (pymixef.model.Model method) (pymixef.pharmacometrics.CompiledModel method) (pymixef.pharmacometrics.dsl.CompiledModel method) (pymixef.pharmacometrics.dsl.ModelDefinition method) (pymixef.pharmacometrics.ModelDefinition method) explain_formula() (in module pymixef.formula) explanation() (pymixef.formula.DesignMatrices method) Exponential (class in pymixef.families) ExponentialSurvival (in module pymixef.families) export_pharmml() (in module pymixef.interoperability) (in module pymixef.interoperability.pharmml) export_sbml() (in module pymixef.interoperability) (in module pymixef.interoperability.sbml) export_sedml() (in module pymixef.interoperability) (in module pymixef.interoperability.sedml) Expr (class in pymixef.pharmacometrics) (class in pymixef.pharmacometrics.dsl) expression (pymixef.Fixed attribute) (pymixef.ir.FixedEffectIR attribute) (pymixef.ir.OutputIR attribute) (pymixef.ir.PredictorIR attribute) (pymixef.model.Fixed attribute) (pymixef.model.Random attribute) (pymixef.pharmacometrics.DifferentialEquation attribute) (pymixef.pharmacometrics.dsl.DifferentialEquation attribute) (pymixef.Random attribute) extra (pymixef.FitResult attribute) (pymixef.results.FitResult attribute) extras (pymixef.pharmacometrics.CanonicalEvent attribute) (pymixef.pharmacometrics.events.CanonicalEvent attribute) F factor() (pymixef.transforms.CholeskyCovarianceTransform method) factor_levels (pymixef.data.DataAudit attribute) (pymixef.formula.DesignMatrices attribute) (pymixef.formula.FormulaExplanation attribute) factor_ordered (pymixef.data.DataAudit attribute) factorize() (in module pymixef.backends.base) failed_groups (pymixef.diagnostics.GroupInfluenceResult property) (pymixef.GroupInfluenceResult property) failed_replicates (pymixef.BootstrapResult property) (pymixef.inference.BootstrapResult property) failed_scenarios (pymixef.ApproximationSensitivityResult property) (pymixef.compare.ApproximationSensitivityResult property) failures (pymixef.ApproximationSensitivityResult attribute) (pymixef.BootstrapResult attribute) (pymixef.compare.ApproximationSensitivityResult attribute) (pymixef.diagnostics.GroupInfluenceResult attribute) (pymixef.GroupInfluenceResult attribute) (pymixef.inference.BootstrapResult attribute) Family (class in pymixef.families) family (pymixef.ir.LikelihoodIR attribute) (pymixef.ir.ModelIR attribute) (pymixef.Model attribute) (pymixef.model.Model attribute) (pymixef.ModelIR attribute) field() (in module pymixef.backends.base) fields (pymixef.ir.EventIR attribute) find_conditional_mode() (in module pymixef.pharmacometrics) (in module pymixef.pharmacometrics.estimation) find_duplicate_keys() (in module pymixef.data) findings (pymixef.model.ValidationReport attribute) fingerprint (pymixef.data.ColumnarData property) fingerprint_data() (in module pymixef.provenance) fingerprint_model_ir() (in module pymixef.provenance) finite_difference_gradient() (in module pymixef.pharmacometrics) (in module pymixef.pharmacometrics.estimation) finite_difference_hessian() (in module pymixef.pharmacometrics) (in module pymixef.pharmacometrics.estimation) finite_difference_sensitivities() (in module pymixef.pharmacometrics) (in module pymixef.pharmacometrics.ode) finite_gradient() (in module pymixef.backends.base) finite_hessian() (in module pymixef.backends.base) fit() (in module pymixef) (in module pymixef.model) (pymixef.backends.Backend method) (pymixef.backends.base.Backend method) (pymixef.backends.GaussianLMMBackend method) (pymixef.backends.glmm.LaplaceGLMMBackend method) (pymixef.backends.LaplaceGLMMBackend method) (pymixef.backends.lmm.GaussianLMMBackend method) (pymixef.backends.mmrm.MMRMBackend method) (pymixef.backends.MMRMBackend method) (pymixef.ExecutionPlan method) (pymixef.Model method) (pymixef.model.ExecutionPlan method) (pymixef.model.Model method) (pymixef.plugins.EstimatorPlugin method) fit_focei() (in module pymixef.pharmacometrics) (in module pymixef.pharmacometrics.estimation) fit_glmm() (in module pymixef.backends) (in module pymixef.backends.glmm) fit_lmm() (in module pymixef.backends) (in module pymixef.backends.lmm) fit_mmrm() (in module pymixef.backends) (in module pymixef.backends.mmrm) FitResult (class in pymixef) (class in pymixef.results) fits (pymixef.ApproximationSensitivityResult attribute) (pymixef.compare.ApproximationSensitivityResult attribute) fitted_values (pymixef.FitResult attribute) (pymixef.results.FitResult attribute) Fixed (class in pymixef) (class in pymixef.model) fixed (pymixef.formula.DesignMatrices attribute) (pymixef.ir.ParameterIR attribute) (pymixef.Model attribute) (pymixef.model.Model attribute) Fixed effect fixed_effects (pymixef.ir.ModelIR attribute) (pymixef.ModelIR attribute) fixed_names (pymixef.backends.base.CompiledData attribute) (pymixef.formula.DesignMatrices attribute) (pymixef.formula.FormulaExplanation attribute) fixed_rank (pymixef.formula.FormulaExplanation attribute) fixed_shape (pymixef.formula.FormulaExplanation attribute) fixed_terms (pymixef.formula.FormulaSpec attribute) FixedEffectIR (class in pymixef.ir) FOCEI for_subject() (pymixef.pharmacometrics.events.EventTable method) (pymixef.pharmacometrics.EventTable method) format() (pymixef.pharmacometrics.DifferentialEquation method) (pymixef.pharmacometrics.dsl.DifferentialEquation method) (pymixef.pharmacometrics.dsl.Expr method) (pymixef.pharmacometrics.Expr method) formula (pymixef.formula.FormulaExplanation attribute) (pymixef.formula.FormulaSpec property) (pymixef.ir.ModelIR attribute) (pymixef.Model attribute) (pymixef.model.Model attribute) (pymixef.ModelIR attribute) formula_text() (pymixef.Model method) (pymixef.model.Model method) FormulaError, [1] FormulaExplanation (class in pymixef.formula) formulas (pymixef.ir.LikelihoodIR attribute) FormulaSpec (class in pymixef.formula) forward (pymixef.pharmacometrics.ode.SensitivityCheck attribute) (pymixef.pharmacometrics.SensitivityCheck attribute) forward() (pymixef.transforms.BoundedTransform method) (pymixef.transforms.CholeskyCovarianceTransform method) (pymixef.transforms.IdentityTransform method) (pymixef.transforms.LogTransform method) (pymixef.transforms.OrderedTransform method) (pymixef.transforms.SimplexTransform method) (pymixef.transforms.SoftplusTransform method) (pymixef.transforms.Transform method) from_components() (pymixef.pharmacometrics.CombinedError class method) (pymixef.pharmacometrics.pk.CombinedError class method) from_dict() (pymixef.convergence.ConvergenceReport class method) (pymixef.ConvergenceReport class method) (pymixef.diagnostics.DiagnosticTable class method) (pymixef.FitResult class method) (pymixef.ir.ModelIR class method) (pymixef.ModelIR class method) (pymixef.provenance.RunManifest class method) (pymixef.results.FitResult class method) (pymixef.RunManifest class method) from_formula() (pymixef.Model class method) (pymixef.model.Model class method) from_json() (pymixef.ir.ModelIR class method) (pymixef.ModelIR class method) from_matrix() (pymixef.convergence.HessianDiagnostics class method) (pymixef.HessianDiagnostics class method) from_records() (pymixef.pharmacometrics.events.EventTable class method) (pymixef.pharmacometrics.EventTable class method) function_evaluations (pymixef.pharmacometrics.ConditionalModeResult attribute) (pymixef.pharmacometrics.estimation.ConditionalModeResult attribute) G Gamma (class in pymixef.families) Gaussian (class in pymixef.families) GaussianLMMBackend (class in pymixef.backends) (class in pymixef.backends.lmm) GeneralizedPoisson (class in pymixef.families) generated (pymixef.pharmacometrics.CanonicalEvent attribute) (pymixef.pharmacometrics.events.CanonicalEvent attribute) generated_additional_doses (pymixef.pharmacometrics.ode.ODESolverMetadata attribute) (pymixef.pharmacometrics.ODESolverMetadata attribute) generated_infusion_stops (pymixef.pharmacometrics.ode.ODESolverMetadata attribute) (pymixef.pharmacometrics.ODESolverMetadata attribute) generation (pymixef.pharmacometrics.CanonicalEvent attribute) (pymixef.pharmacometrics.events.CanonicalEvent attribute) generator() (pymixef.random.RandomStreamManager method) (pymixef.RandomStreamManager method) GenPoisson (in module pymixef.families) get() (pymixef.plugins.Registry method) get_backend() (in module pymixef.backends) get_capability() (in module pymixef) (in module pymixef.capabilities) get_covariance() (in module pymixef.covariance) get_link() (in module pymixef.families) get_transform() (in module pymixef.transforms) GLMM GLMMBackend (in module pymixef.backends) (in module pymixef.backends.glmm) Gompertz (class in pymixef.families) GompertzSurvival (in module pymixef.families) gradient (pymixef.pharmacometrics.ConditionalModeResult attribute) (pymixef.pharmacometrics.estimation.ConditionalModeResult attribute) gradient_evaluations (pymixef.convergence.ConvergenceReport attribute) (pymixef.ConvergenceReport attribute) gradient_norm (pymixef.pharmacometrics.ConditionalModeResult attribute) (pymixef.pharmacometrics.estimation.ConditionalModeResult attribute) group (pymixef.formula.RandomDesignBlock property) (pymixef.formula.RandomTerm attribute) (pymixef.ir.CovarianceIR attribute) (pymixef.ir.RandomEffectIR attribute) (pymixef.model.Random attribute) (pymixef.Random attribute) group_codes (pymixef.backends.base.RandomBlockData attribute) (pymixef.formula.RandomDesignBlock attribute) group_column (pymixef.diagnostics.GroupInfluenceResult attribute) (pymixef.GroupInfluenceResult attribute) group_influence() (in module pymixef) (in module pymixef.diagnostics) group_labels (pymixef.formula.RandomDesignBlock attribute) group_levels (pymixef.backends.base.RandomBlockData attribute) (pymixef.formula.RandomDesignBlock attribute) GroupInfluenceResult (class in pymixef) (class in pymixef.diagnostics) groups (pymixef.formula.RandomDesignBlock property) H hash (pymixef.ir.ModelIR property) (pymixef.ModelIR property) hessian (pymixef.convergence.ConvergenceReport attribute) (pymixef.ConvergenceReport attribute) (pymixef.pharmacometrics.ConditionalModeResult attribute) (pymixef.pharmacometrics.estimation.ConditionalModeResult attribute) hessian_positive_definite (pymixef.pharmacometrics.ConditionalModeResult attribute) (pymixef.pharmacometrics.estimation.ConditionalModeResult attribute) HessianDiagnostics (class in pymixef) (class in pymixef.convergence) HeterogeneousAR1 (class in pymixef.covariance) HeterogeneousAR1Covariance (in module pymixef.covariance) HeterogeneousToeplitz (class in pymixef.covariance) HeterogeneousToeplitzCovariance (in module pymixef.covariance) Hurdle (class in pymixef.families) HurdleFamily (in module pymixef.families) I ID (pymixef.pharmacometrics.CanonicalEvent property) id (pymixef.pharmacometrics.CanonicalEvent property) ID (pymixef.pharmacometrics.events.CanonicalEvent property) id (pymixef.pharmacometrics.events.CanonicalEvent property) identifier (pymixef.capabilities.Capability attribute) identity (pymixef.families.links attribute) IdentityTransform (class in pymixef.transforms) II (pymixef.pharmacometrics.CanonicalEvent property) ii (pymixef.pharmacometrics.CanonicalEvent property) II (pymixef.pharmacometrics.events.CanonicalEvent property) ii (pymixef.pharmacometrics.events.CanonicalEvent property) implementation (pymixef.plugins.PluginInfo attribute) implemented (pymixef.capabilities.Capability attribute) (pymixef.validation.TraceabilityRecord attribute) import_nonmem_data() (in module pymixef.interoperability) (in module pymixef.interoperability.nonmem) import_nonmem_table() (in module pymixef.interoperability) (in module pymixef.interoperability.nonmem) import_pharmml() (in module pymixef.interoperability) (in module pymixef.interoperability.pharmml) import_sbml() (in module pymixef.interoperability) (in module pymixef.interoperability.sbml) import_sedml() (in module pymixef.interoperability) (in module pymixef.interoperability.sedml) imputed_column (pymixef.data.PatternMixtureResult attribute) (pymixef.PatternMixtureResult attribute) include_constants (pymixef.pharmacometrics.ConditionalObjective attribute) (pymixef.pharmacometrics.estimation.ConditionalObjective attribute) independent() (pymixef.pharmacometrics.dsl.Eta class method) (pymixef.pharmacometrics.Eta class method) index (pymixef.ir.CovarianceIR attribute) info() (pymixef.plugins.Registry method) infusion() (pymixef.pharmacometrics.OneCompartmentPK method) (pymixef.pharmacometrics.pk.OneCompartmentPK method) (pymixef.pharmacometrics.pk.TwoCompartmentPK method) (pymixef.pharmacometrics.TwoCompartmentPK method) infusion_duration (pymixef.pharmacometrics.CanonicalEvent property) (pymixef.pharmacometrics.events.CanonicalEvent property) infusion_rates (pymixef.pharmacometrics.ode.ODEContext attribute) (pymixef.pharmacometrics.ODEContext attribute) INFUSION_STOP (pymixef.pharmacometrics.events.EventType attribute) (pymixef.pharmacometrics.EventType attribute) init (pymixef.pharmacometrics.dsl.Param attribute) (pymixef.pharmacometrics.Param attribute) initial (pymixef.ir.ParameterIR attribute) (pymixef.ir.StateEquationIR attribute) (pymixef.pharmacometrics.dsl.State attribute) (pymixef.pharmacometrics.State attribute) initial() (pymixef.backends.base.CovarianceParameterization method) initial_latent (pymixef.pharmacometrics.estimation.SAEMProblem attribute) (pymixef.pharmacometrics.SAEMProblem attribute) initial_parameters (pymixef.pharmacometrics.estimation.SAEMProblem attribute) (pymixef.pharmacometrics.SAEMProblem attribute) input_position (pymixef.data.AuditRecord attribute) (pymixef.data.PatternMixtureRecord attribute) input_rows (pymixef.data.DataAudit attribute) InputAdapter() (in module pymixef.data) Integrity hash intercept (pymixef.formula.FormulaSpec attribute) (pymixef.formula.RandomTerm attribute) InterchangeResult (class in pymixef.interoperability) (class in pymixef.interoperability.base) intercompartmental_clearance (pymixef.pharmacometrics.pk.TwoCompartmentPK attribute) (pymixef.pharmacometrics.TwoCompartmentPK attribute) interval (pymixef.pharmacometrics.CanonicalEvent attribute) (pymixef.pharmacometrics.events.CanonicalEvent attribute) interval_censored_loglikelihood() (in module pymixef.pharmacometrics) (in module pymixef.pharmacometrics.pk) intervals() (pymixef.BootstrapResult method) (pymixef.inference.BootstrapResult method) into() (pymixef.pharmacometrics.Dose class method) (pymixef.pharmacometrics.dsl.Dose class method) INVALID_RECORD (pymixef.data.MissingnessKind attribute) inverse (pymixef.families.links attribute) inverse() (pymixef.families.Link method) (pymixef.transforms.BoundedTransform method) (pymixef.transforms.CholeskyCovarianceTransform method) (pymixef.transforms.IdentityTransform method) (pymixef.transforms.LogTransform method) (pymixef.transforms.OrderedTransform method) (pymixef.transforms.SimplexTransform method) (pymixef.transforms.SoftplusTransform method) (pymixef.transforms.Transform method) inverse_squared (pymixef.families.links attribute) InverseGauss (in module pymixef.families) InverseGaussian (class in pymixef.families) IRNode (class in pymixef.ir) IRValidationError, [1] IRVersionError, [1] is_dose (pymixef.pharmacometrics.CanonicalEvent property) (pymixef.pharmacometrics.events.CanonicalEvent property) is_infusion (pymixef.pharmacometrics.CanonicalEvent property) (pymixef.pharmacometrics.events.CanonicalEvent property) is_missing() (in module pymixef.data) is_observation (pymixef.pharmacometrics.CanonicalEvent property) (pymixef.pharmacometrics.events.CanonicalEvent property) is_reset (pymixef.pharmacometrics.CanonicalEvent property) (pymixef.pharmacometrics.events.CanonicalEvent property) issues (pymixef.interoperability.base.CompatibilityReport attribute) (pymixef.interoperability.CompatibilityReport attribute) issues() (in module pymixef.interoperability.base) iter_capabilities() (in module pymixef) (in module pymixef.capabilities) iterations (pymixef.convergence.ConvergenceReport attribute) (pymixef.ConvergenceReport attribute) (pymixef.pharmacometrics.ConditionalModeResult attribute) (pymixef.pharmacometrics.estimation.ConditionalModeResult attribute) (pymixef.pharmacometrics.estimation.SAEMControl attribute) (pymixef.pharmacometrics.SAEMControl attribute) iv_bolus() (pymixef.pharmacometrics.OneCompartmentPK method) (pymixef.pharmacometrics.pk.OneCompartmentPK method) (pymixef.pharmacometrics.pk.TwoCompartmentPK method) (pymixef.pharmacometrics.TwoCompartmentPK method) J jacobian() (pymixef.transforms.Transform method) K k10 (pymixef.pharmacometrics.pk.TwoCompartmentRates attribute) (pymixef.pharmacometrics.TwoCompartmentRates attribute) k12 (pymixef.pharmacometrics.pk.TwoCompartmentRates attribute) (pymixef.pharmacometrics.TwoCompartmentRates attribute) k21 (pymixef.pharmacometrics.pk.TwoCompartmentRates attribute) (pymixef.pharmacometrics.TwoCompartmentRates attribute) keep_latent_trace (pymixef.pharmacometrics.estimation.SAEMControl attribute) (pymixef.pharmacometrics.SAEMControl attribute) kind (pymixef.ir.PredictorIR attribute) (pymixef.ir.TransformIR attribute) (pymixef.pharmacometrics.CanonicalEvent property) (pymixef.pharmacometrics.events.CanonicalEvent property) known_matrix (pymixef.ir.RandomEffectIR attribute) KnownCovariance (class in pymixef.covariance) L lag (pymixef.pharmacometrics.CanonicalEvent attribute) (pymixef.pharmacometrics.Dose attribute) (pymixef.pharmacometrics.dsl.Dose attribute) (pymixef.pharmacometrics.events.CanonicalEvent attribute) Laplace approximation laplace_population_objective() (in module pymixef.pharmacometrics) (in module pymixef.pharmacometrics.estimation) LaplaceGLMMBackend (class in pymixef.backends) (class in pymixef.backends.glmm) LaplacePopulationResult (class in pymixef.pharmacometrics) (class in pymixef.pharmacometrics.estimation) latent (pymixef.pharmacometrics.estimation.SAEMResult attribute) (pymixef.pharmacometrics.SAEMResult attribute) latent_trace (pymixef.pharmacometrics.estimation.SAEMResult attribute) (pymixef.pharmacometrics.SAEMResult attribute) left_censored_loglikelihood() (in module pymixef.pharmacometrics) (in module pymixef.pharmacometrics.pk) level (pymixef.pharmacometrics.dsl.Eta attribute) (pymixef.pharmacometrics.Eta attribute) levels (pymixef.data.ColumnSchema attribute) library_path() (in module pymixef.native) LikelihoodIR (class in pymixef.ir) likelihoods (pymixef.ir.ModelIR attribute) (pymixef.ModelIR attribute) limitations (pymixef.capabilities.Capability attribute) (pymixef.validation.TraceabilityRecord attribute) linear_inference() (in module pymixef.backends.mmrm) Link (class in pymixef.families) link (pymixef.ir.LikelihoodIR attribute) links (class in pymixef.families) lloq (pymixef.pharmacometrics.CanonicalEvent attribute) LLOQ (pymixef.pharmacometrics.CanonicalEvent property) lloq (pymixef.pharmacometrics.events.CanonicalEvent attribute) LLOQ (pymixef.pharmacometrics.events.CanonicalEvent property) lloq (pymixef.pharmacometrics.EventSnapshot attribute) (pymixef.pharmacometrics.ode.EventSnapshot attribute) LMM LMMBackend (in module pymixef.backends) (in module pymixef.backends.lmm) load() (in module pymixef) (pymixef.diagnostics.DiagnosticTable class method) (pymixef.FitResult class method) (pymixef.results.FitResult class method) load_warning_catalog() (in module pymixef.warnings) log (pymixef.families.links attribute) log() (in module pymixef.pharmacometrics) (in module pymixef.pharmacometrics.dsl) log1p() (in module pymixef.pharmacometrics) (in module pymixef.pharmacometrics.dsl) log_abs_det_jacobian() (pymixef.transforms.BoundedTransform method) (pymixef.transforms.CholeskyCovarianceTransform method) (pymixef.transforms.IdentityTransform method) (pymixef.transforms.LogTransform method) (pymixef.transforms.OrderedTransform method) (pymixef.transforms.SimplexTransform method) (pymixef.transforms.SoftplusTransform method) (pymixef.transforms.Transform method) log_density() (pymixef.families.Exponential method) (pymixef.families.Gompertz method) (pymixef.families.LogLogistic method) (pymixef.families.LogNormalSurvival method) (pymixef.families.PiecewiseExponential method) (pymixef.families.Weibull method) log_joint (pymixef.pharmacometrics.estimation.SAEMProblem attribute) (pymixef.pharmacometrics.SAEMProblem attribute) log_likelihood (pymixef.FitResult attribute) (pymixef.results.FitResult attribute) log_prob() (pymixef.families.Bernoulli method) (pymixef.families.Beta method) (pymixef.families.Binomial method) (pymixef.families.Censored method) (pymixef.families.COMPoisson method) (pymixef.families.Family method) (pymixef.families.Gamma method) (pymixef.families.Gaussian method) (pymixef.families.GeneralizedPoisson method) (pymixef.families.Hurdle method) (pymixef.families.InverseGaussian method) (pymixef.families.LogNormal method) (pymixef.families.Multinomial method) (pymixef.families.NegativeBinomial2 method) (pymixef.families.Ordinal method) (pymixef.families.Poisson method) (pymixef.families.StudentT method) (pymixef.families.Truncated method) (pymixef.families.Tweedie method) (pymixef.families.ZeroInflated method) log_probability() (pymixef.families.Family method) logcdf() (pymixef.families.Beta method) (pymixef.families.Family method) (pymixef.families.Gamma method) (pymixef.families.Gaussian method) (pymixef.families.InverseGaussian method) (pymixef.families.LogNormal method) (pymixef.families.StudentT method) logdet_from_cholesky() (in module pymixef.backends.base) logit (pymixef.families.links attribute) LogLogistic (class in pymixef.families) LogLogisticSurvival (in module pymixef.families) LogNormal (class in pymixef.families) Lognormal (in module pymixef.families) lognormal() (in module pymixef.pharmacometrics) (in module pymixef.pharmacometrics.pk) LogNormalError (class in pymixef.pharmacometrics) (class in pymixef.pharmacometrics.pk) LogNormalSurvival (class in pymixef.families) logpdf() (pymixef.families.Family method) (pymixef.pharmacometrics.LogNormalError method) (pymixef.pharmacometrics.pk.LogNormalError method) logpmf() (pymixef.families.Family method) logsf() (pymixef.families.Beta method) (pymixef.families.Exponential method) (pymixef.families.Family method) (pymixef.families.Gamma method) (pymixef.families.Gaussian method) (pymixef.families.Gompertz method) (pymixef.families.InverseGaussian method) (pymixef.families.LogLogistic method) (pymixef.families.LogNormal method) (pymixef.families.LogNormalSurvival method) (pymixef.families.PiecewiseExponential method) (pymixef.families.StudentT method) (pymixef.families.Weibull method) LogTransform (class in pymixef.transforms) lower (pymixef.pharmacometrics.dsl.Param attribute) (pymixef.pharmacometrics.Param attribute) (pymixef.transforms.BoundedTransform attribute) lower_limits (pymixef.pharmacometrics.ConditionalObjective attribute) (pymixef.pharmacometrics.estimation.ConditionalObjective attribute) M m_step (pymixef.pharmacometrics.estimation.SAEMProblem attribute) (pymixef.pharmacometrics.SAEMProblem attribute) main() (in module pymixef.cli) make_payload() (in module pymixef.backends.base) Manifest manifest (pymixef.FitResult attribute) (pymixef.results.FitResult attribute) manifest_schema_version (pymixef.provenance.RunManifest attribute) (pymixef.RunManifest attribute) Marginal prediction materiality (pymixef.ApproximationSensitivityResult attribute) (pymixef.compare.ApproximationSensitivityResult attribute) matrices (pymixef.ExecutionPlan attribute) (pymixef.model.ExecutionPlan attribute) matrix (pymixef.formula.RandomDesignBlock attribute) matrix() (pymixef.backends.base.CovarianceParameterization method) (pymixef.covariance.CovarianceStructure method) Maturity (class in pymixef) maturity (pymixef.capabilities.Capability attribute) (pymixef.validation.TraceabilityRecord attribute) max_eigenvalue (pymixef.convergence.HessianDiagnostics attribute) (pymixef.HessianDiagnostics attribute) max_step (pymixef.pharmacometrics.ode.ODESolverMetadata attribute) (pymixef.pharmacometrics.ODESolverMetadata attribute) maximum_scaled_difference (pymixef.pharmacometrics.ode.SensitivityCheck attribute) (pymixef.pharmacometrics.SensitivityCheck attribute) mcmc_steps (pymixef.pharmacometrics.estimation.SAEMControl attribute) (pymixef.pharmacometrics.SAEMControl attribute) mdv (pymixef.pharmacometrics.CanonicalEvent attribute) MDV (pymixef.pharmacometrics.CanonicalEvent property) mdv (pymixef.pharmacometrics.events.CanonicalEvent attribute) MDV (pymixef.pharmacometrics.events.CanonicalEvent property) mdv (pymixef.pharmacometrics.EventSnapshot attribute) (pymixef.pharmacometrics.ode.EventSnapshot attribute) mean (pymixef.pharmacometrics.dsl.Observation attribute) (pymixef.pharmacometrics.Observation attribute) mean() (pymixef.families.Bernoulli method) (pymixef.families.Beta method) (pymixef.families.Binomial method) (pymixef.families.COMPoisson method) (pymixef.families.Exponential method) (pymixef.families.Family method) (pymixef.families.Gamma method) (pymixef.families.Gaussian method) (pymixef.families.GeneralizedPoisson method) (pymixef.families.Gompertz method) (pymixef.families.Hurdle method) (pymixef.families.InverseGaussian method) (pymixef.families.LogLogistic method) (pymixef.families.LogNormal method) (pymixef.families.LogNormalSurvival method) (pymixef.families.Multinomial method) (pymixef.families.NegativeBinomial2 method) (pymixef.families.Ordinal method) (pymixef.families.PiecewiseExponential method) (pymixef.families.Poisson method) (pymixef.families.StudentT method) (pymixef.families.Tweedie method) (pymixef.families.Weibull method) (pymixef.families.ZeroInflated method) message (pymixef.model.ValidationFinding attribute) (pymixef.pharmacometrics.ConditionalModeResult attribute) (pymixef.pharmacometrics.dsl.ValidationMessage attribute) (pymixef.pharmacometrics.estimation.ConditionalModeResult attribute) (pymixef.pharmacometrics.ode.ODESolverMetadata attribute) (pymixef.pharmacometrics.ODESolverMetadata attribute) (pymixef.pharmacometrics.ValidationMessage attribute) (pymixef.WarningRecord attribute) messages (pymixef.pharmacometrics.dsl.ModelValidation attribute) (pymixef.pharmacometrics.ModelValidation attribute) metadata (pymixef.diagnostics.DiagnosticTable attribute) (pymixef.interoperability.base.CompatibilityReport attribute) (pymixef.interoperability.CompatibilityReport attribute) (pymixef.ir.ModelIR attribute) (pymixef.Model attribute) (pymixef.model.Model attribute) (pymixef.ModelIR attribute) (pymixef.pharmacometrics.dsl.Expr attribute) (pymixef.pharmacometrics.dsl.Observation attribute) (pymixef.pharmacometrics.Expr attribute) (pymixef.pharmacometrics.Observation attribute) (pymixef.pharmacometrics.ode.ODESimulationResult attribute) (pymixef.pharmacometrics.ODESimulationResult attribute) method (pymixef.ExecutionPlan attribute) (pymixef.FitResult attribute) (pymixef.model.ExecutionPlan attribute) (pymixef.model.ValidationReport attribute) (pymixef.provenance.RunManifest attribute) (pymixef.results.FitResult attribute) (pymixef.RunManifest attribute) migrate_ir() (in module pymixef.ir) min_eigenvalue (pymixef.convergence.HessianDiagnostics attribute) (pymixef.HessianDiagnostics attribute) missing_count (pymixef.data.ColumnSchema attribute) MISSING_COVARIATE (pymixef.data.MissingnessKind attribute) missing_mask() (in module pymixef.data) MISSING_RESPONSE (pymixef.data.MissingnessKind attribute) missingness (pymixef.data.AuditRecord attribute) MissingnessKind (class in pymixef.data) MMRM MMRMBackend (class in pymixef.backends) (class in pymixef.backends.mmrm) Model (class in pymixef) (class in pymixef.model) model (pymixef.ExecutionPlan attribute) (pymixef.model.ExecutionPlan attribute) model() (in module pymixef.pharmacometrics) (in module pymixef.pharmacometrics.dsl) model_diff() (in module pymixef.ir) model_ir (pymixef.ExecutionPlan attribute) (pymixef.FitResult attribute) (pymixef.model.ExecutionPlan attribute) (pymixef.results.FitResult attribute) model_ir_hash (pymixef.provenance.RunManifest attribute) (pymixef.RunManifest attribute) model_matrix() (in module pymixef.formula) ModelDefinition (class in pymixef.pharmacometrics) (class in pymixef.pharmacometrics.dsl) ModelDiff (class in pymixef.ir) ModelIR (class in pymixef) (class in pymixef.ir) ModelValidation (class in pymixef.pharmacometrics) (class in pymixef.pharmacometrics.dsl) modes (pymixef.pharmacometrics.estimation.LaplacePopulationResult attribute) (pymixef.pharmacometrics.LaplacePopulationResult attribute) module pymixef pymixef.backends pymixef.backends.base pymixef.backends.glmm pymixef.backends.lmm pymixef.backends.mmrm pymixef.capabilities pymixef.cli pymixef.compare pymixef.convergence pymixef.covariance pymixef.data pymixef.diagnostics pymixef.errors pymixef.families pymixef.formula pymixef.inference pymixef.interoperability pymixef.interoperability.base pymixef.interoperability.nonmem pymixef.interoperability.pharmml pymixef.interoperability.r pymixef.interoperability.sbml pymixef.interoperability.sedml pymixef.ir pymixef.model pymixef.native pymixef.pharmacometrics pymixef.pharmacometrics.dsl pymixef.pharmacometrics.estimation pymixef.pharmacometrics.events pymixef.pharmacometrics.ode pymixef.pharmacometrics.pk pymixef.plugins pymixef.provenance pymixef.random pymixef.reporting pymixef.results pymixef.transforms pymixef.validation pymixef.warnings moments() (pymixef.families.Family method) Multinomial (class in pymixef.families) N n_columns (pymixef.data.ColumnarData property) n_fixed (pymixef.backends.base.CompiledData property) n_groups (pymixef.backends.base.RandomBlockData property) n_obs (pymixef.backends.base.CompiledData property) n_observations (pymixef.FitResult property) (pymixef.results.FitResult property) n_rows (pymixef.data.ColumnarData property) (pymixef.formula.FormulaExplanation attribute) name (pymixef.backends.Backend attribute) (pymixef.backends.base.Backend attribute) (pymixef.backends.base.RandomBlockData attribute) (pymixef.backends.GaussianLMMBackend attribute) (pymixef.backends.glmm.LaplaceGLMMBackend attribute) (pymixef.backends.LaplaceGLMMBackend attribute) (pymixef.backends.lmm.GaussianLMMBackend attribute) (pymixef.backends.mmrm.MMRMBackend attribute) (pymixef.backends.MMRMBackend attribute) (pymixef.capabilities.Capability attribute) (pymixef.covariance.AnteDependence attribute) (pymixef.covariance.AR1 attribute) (pymixef.covariance.CompoundSymmetry attribute) (pymixef.covariance.CovarianceStructure attribute) (pymixef.covariance.Diagonal attribute) (pymixef.covariance.HeterogeneousAR1 attribute) (pymixef.covariance.HeterogeneousToeplitz attribute) (pymixef.covariance.KnownCovariance attribute) (pymixef.covariance.SpatialPower attribute) (pymixef.covariance.Toeplitz attribute) (pymixef.covariance.Unstructured attribute) (pymixef.data.ColumnSchema attribute) (pymixef.diagnostics.DiagnosticTable attribute) (pymixef.families.Bernoulli attribute) (pymixef.families.Beta attribute) (pymixef.families.Binomial attribute) (pymixef.families.Censored attribute) (pymixef.families.COMPoisson attribute) (pymixef.families.Exponential attribute) (pymixef.families.Family attribute) (pymixef.families.Gamma attribute) (pymixef.families.Gaussian attribute) (pymixef.families.GeneralizedPoisson attribute) (pymixef.families.Gompertz attribute) (pymixef.families.Hurdle attribute) (pymixef.families.InverseGaussian attribute) (pymixef.families.Link attribute) (pymixef.families.LogLogistic attribute) (pymixef.families.LogNormal attribute) (pymixef.families.LogNormalSurvival attribute) (pymixef.families.Multinomial attribute) (pymixef.families.NegativeBinomial1 attribute) (pymixef.families.NegativeBinomial2 attribute) (pymixef.families.Ordinal attribute) (pymixef.families.PiecewiseExponential attribute) (pymixef.families.Poisson attribute) (pymixef.families.StudentT attribute) (pymixef.families.Truncated attribute) (pymixef.families.Tweedie attribute) (pymixef.families.Weibull attribute) (pymixef.families.ZeroInflated attribute) (pymixef.formula.RandomDesignBlock attribute) (pymixef.ir.FixedEffectIR attribute) (pymixef.ir.ModelIR attribute) (pymixef.ir.OutputIR attribute) (pymixef.ir.ParameterIR attribute) (pymixef.ir.PredictorIR attribute) (pymixef.ir.TransformIR attribute) (pymixef.model.Response attribute) (pymixef.ModelIR attribute) (pymixef.pharmacometrics.CompiledModel attribute) (pymixef.pharmacometrics.dsl.CompiledModel attribute) (pymixef.pharmacometrics.dsl.Eta attribute) (pymixef.pharmacometrics.dsl.Param attribute) (pymixef.pharmacometrics.dsl.State attribute) (pymixef.pharmacometrics.dsl.Symbol attribute) (pymixef.pharmacometrics.Eta attribute) (pymixef.pharmacometrics.Param attribute) (pymixef.pharmacometrics.State attribute) (pymixef.pharmacometrics.Symbol attribute) (pymixef.plugins.PluginInfo attribute) (pymixef.Response attribute) (pymixef.transforms.BoundedTransform attribute) (pymixef.transforms.CholeskyCovarianceTransform attribute) (pymixef.transforms.IdentityTransform attribute) (pymixef.transforms.LogTransform attribute) (pymixef.transforms.OrderedTransform attribute) (pymixef.transforms.SimplexTransform attribute) (pymixef.transforms.SoftplusTransform attribute) (pymixef.transforms.Transform attribute) names() (pymixef.plugins.Registry method) names_and_values() (pymixef.backends.base.CovarianceParameterization method) namespace (pymixef.random.RandomStreamManager attribute) (pymixef.RandomStreamManager attribute) native_available() (in module pymixef.native) NB1 (in module pymixef.families) NB2 (in module pymixef.families) near_singular (pymixef.covariance.CovarianceValidation attribute) NegativeBinomial (in module pymixef.families) NegativeBinomial1 (class in pymixef.families) NegativeBinomial2 (class in pymixef.families) nfev (pymixef.pharmacometrics.ode.ODESolverMetadata attribute) (pymixef.pharmacometrics.ODESolverMetadata attribute) njev (pymixef.pharmacometrics.ode.ODESolverMetadata attribute) (pymixef.pharmacometrics.ODESolverMetadata attribute) nlu (pymixef.pharmacometrics.ode.ODESolverMetadata attribute) (pymixef.pharmacometrics.ODESolverMetadata attribute) node_type (pymixef.ir.CovarianceIR attribute) (pymixef.ir.EventIR attribute) (pymixef.ir.FixedEffectIR attribute) (pymixef.ir.IRNode attribute) (pymixef.ir.LikelihoodIR attribute) (pymixef.ir.OutputIR attribute) (pymixef.ir.ParameterIR attribute) (pymixef.ir.PredictorIR attribute) (pymixef.ir.PriorIR attribute) (pymixef.ir.RandomEffectIR attribute) (pymixef.ir.StateEquationIR attribute) (pymixef.ir.TransformIR attribute) Normal (in module pymixef.families) normalize() (pymixef.plugins.Registry static method) normalized (pymixef.families.Family attribute) NOT_APPLICABLE (pymixef.pharmacometrics.DoseAmountStatus attribute) (pymixef.pharmacometrics.events.DoseAmountStatus attribute) NumericalWarning O objective (pymixef.FitResult attribute) (pymixef.pharmacometrics.ConditionalModeResult attribute) (pymixef.pharmacometrics.estimation.ConditionalModeResult attribute) (pymixef.pharmacometrics.estimation.LaplacePopulationResult attribute) (pymixef.pharmacometrics.LaplacePopulationResult attribute) (pymixef.results.FitResult attribute) objective_difference (pymixef.compare.ComparisonResult attribute) (pymixef.ComparisonResult attribute) objective_evaluations (pymixef.convergence.ConvergenceReport attribute) (pymixef.ConvergenceReport attribute) ObjectiveComponents (class in pymixef.pharmacometrics) (class in pymixef.pharmacometrics.estimation) Observation (class in pymixef.pharmacometrics) (class in pymixef.pharmacometrics.dsl) observation (pymixef.pharmacometrics.estimation.ObjectiveComponents attribute) OBSERVATION (pymixef.pharmacometrics.events.EventType attribute) (pymixef.pharmacometrics.EventType attribute) observation (pymixef.pharmacometrics.ObjectiveComponents attribute) observation_objective (pymixef.pharmacometrics.ConditionalModeResult attribute) (pymixef.pharmacometrics.estimation.ConditionalModeResult attribute) ObservationError (class in pymixef.pharmacometrics) (class in pymixef.pharmacometrics.pk) observations (pymixef.pharmacometrics.CompiledModel attribute) (pymixef.pharmacometrics.ConditionalObjective attribute) (pymixef.pharmacometrics.dsl.CompiledModel attribute) (pymixef.pharmacometrics.estimation.ConditionalObjective attribute) (pymixef.pharmacometrics.ode.ODESimulationResult attribute) (pymixef.pharmacometrics.ODESimulationResult attribute) observe() (in module pymixef.pharmacometrics) (in module pymixef.pharmacometrics.dsl) occasion (pymixef.pharmacometrics.CanonicalEvent attribute) (pymixef.pharmacometrics.events.CanonicalEvent attribute) (pymixef.pharmacometrics.EventSnapshot attribute) (pymixef.pharmacometrics.ode.EventSnapshot attribute) ode_failures (pymixef.convergence.ConvergenceReport attribute) (pymixef.ConvergenceReport attribute) ODEContext (class in pymixef.pharmacometrics) (class in pymixef.pharmacometrics.ode) ODESimulationError, [1] ODESimulationResult (class in pymixef.pharmacometrics) (class in pymixef.pharmacometrics.ode) ODESolverMetadata (class in pymixef.pharmacometrics) (class in pymixef.pharmacometrics.ode) offset (pymixef.backends.base.CompiledData attribute) omega (pymixef.pharmacometrics.ConditionalObjective attribute) (pymixef.pharmacometrics.estimation.ConditionalObjective attribute) omega_from_standard_deviations() (in module pymixef.pharmacometrics) (in module pymixef.pharmacometrics.estimation) one_compartment_bolus() (in module pymixef.pharmacometrics) (in module pymixef.pharmacometrics.pk) one_compartment_infusion() (in module pymixef.pharmacometrics) (in module pymixef.pharmacometrics.pk) one_compartment_iv_bolus() (in module pymixef.pharmacometrics) (in module pymixef.pharmacometrics.pk) one_compartment_iv_infusion() (in module pymixef.pharmacometrics) (in module pymixef.pharmacometrics.pk) one_compartment_oral() (in module pymixef.pharmacometrics) (in module pymixef.pharmacometrics.pk) OneCompartmentPK (class in pymixef.pharmacometrics) (class in pymixef.pharmacometrics.pk) operation (pymixef.pharmacometrics.dsl.Expr attribute) (pymixef.pharmacometrics.Expr attribute) operator (pymixef.formula.RandomTerm property) optimizer_covariance() (in module pymixef.backends.base) optimizer_message (pymixef.convergence.ConvergenceReport attribute) (pymixef.ConvergenceReport attribute) optimizer_terminated (pymixef.convergence.ConvergenceReport attribute) (pymixef.ConvergenceReport attribute) options (pymixef.ir.CovarianceIR attribute) (pymixef.ir.TransformIR attribute) oral() (pymixef.pharmacometrics.OneCompartmentPK method) (pymixef.pharmacometrics.pk.OneCompartmentPK method) (pymixef.pharmacometrics.pk.TwoCompartmentPK method) (pymixef.pharmacometrics.TwoCompartmentPK method) ordered (pymixef.data.ColumnSchema attribute) OrderedTransform (class in pymixef.transforms) Ordinal (class in pymixef.families) OTHER (pymixef.pharmacometrics.events.EventType attribute) (pymixef.pharmacometrics.EventType attribute) output_hashes (pymixef.provenance.RunManifest attribute) (pymixef.RunManifest attribute) output_kind (pymixef.ir.OutputIR attribute) OutputIR (class in pymixef.ir) outputs (pymixef.ir.ModelIR attribute) (pymixef.ModelIR attribute) P package_version (pymixef.provenance.RunManifest attribute) (pymixef.RunManifest attribute) Param (class in pymixef.pharmacometrics) (class in pymixef.pharmacometrics.dsl) parameter (pymixef.BoundaryRecord attribute) (pymixef.convergence.BoundaryRecord attribute) parameter_count() (pymixef.covariance.AnteDependence method) (pymixef.covariance.AR1 method) (pymixef.covariance.CompoundSymmetry method) (pymixef.covariance.CovarianceStructure method) (pymixef.covariance.Diagonal method) (pymixef.covariance.HeterogeneousAR1 method) (pymixef.covariance.HeterogeneousToeplitz method) (pymixef.covariance.KnownCovariance method) (pymixef.covariance.SpatialPower method) (pymixef.covariance.Toeplitz method) (pymixef.covariance.Unstructured method) parameter_covariance (pymixef.FitResult attribute) (pymixef.results.FitResult attribute) parameter_names (pymixef.families.Bernoulli attribute) (pymixef.families.Beta attribute) (pymixef.families.Binomial attribute) (pymixef.families.COMPoisson attribute) (pymixef.families.Exponential attribute) (pymixef.families.Family attribute) (pymixef.families.Gamma attribute) (pymixef.families.Gaussian attribute) (pymixef.families.GeneralizedPoisson attribute) (pymixef.families.Gompertz attribute) (pymixef.families.InverseGaussian attribute) (pymixef.families.LogLogistic attribute) (pymixef.families.LogNormal attribute) (pymixef.families.LogNormalSurvival attribute) (pymixef.families.Multinomial attribute) (pymixef.families.NegativeBinomial2 attribute) (pymixef.families.Ordinal attribute) (pymixef.families.PiecewiseExponential attribute) (pymixef.families.Poisson attribute) (pymixef.families.StudentT attribute) (pymixef.families.Tweedie attribute) (pymixef.families.Weibull attribute) (pymixef.pharmacometrics.estimation.SAEMProblem attribute) (pymixef.pharmacometrics.ode.SensitivityCheck attribute) (pymixef.pharmacometrics.SAEMProblem attribute) (pymixef.pharmacometrics.SensitivityCheck attribute) parameter_names() (pymixef.covariance.AnteDependence method) (pymixef.covariance.AR1 method) (pymixef.covariance.CompoundSymmetry method) (pymixef.covariance.CovarianceStructure method) (pymixef.covariance.Diagonal method) (pymixef.covariance.HeterogeneousAR1 method) (pymixef.covariance.HeterogeneousToeplitz method) (pymixef.covariance.SpatialPower method) (pymixef.covariance.Toeplitz method) (pymixef.covariance.Unstructured method) parameter_step_norm (pymixef.convergence.ConvergenceReport attribute) (pymixef.ConvergenceReport attribute) parameter_trace (pymixef.pharmacometrics.estimation.SAEMResult attribute) (pymixef.pharmacometrics.SAEMResult attribute) ParameterIR (class in pymixef.ir) parameters (pymixef.FitResult attribute) (pymixef.ir.ModelIR attribute) (pymixef.ir.PriorIR attribute) (pymixef.ModelIR attribute) (pymixef.pharmacometrics.CompiledModel attribute) (pymixef.pharmacometrics.dsl.CompiledModel attribute) (pymixef.pharmacometrics.estimation.SAEMResult attribute) (pymixef.pharmacometrics.ode.ODEContext attribute) (pymixef.pharmacometrics.ODEContext attribute) (pymixef.pharmacometrics.SAEMResult attribute) (pymixef.results.FitResult attribute) parse_control_stream() (in module pymixef.interoperability) (in module pymixef.interoperability.nonmem) parse_formula() (in module pymixef.formula) path (pymixef.ir.DiffEntry attribute) pattern_mixture_adjust() (in module pymixef) (in module pymixef.data) PatternMixtureRecord (class in pymixef.data) PatternMixtureResult (class in pymixef) (class in pymixef.data) peripheral_volume (pymixef.pharmacometrics.pk.TwoCompartmentPK attribute) (pymixef.pharmacometrics.TwoCompartmentPK attribute) PiecewiseExponential (class in pymixef.families) PKValidationError, [1] PluginError, [1] PluginInfo (class in pymixef.plugins) Poisson (class in pymixef.families) Population prediction positive() (pymixef.pharmacometrics.dsl.Param class method) (pymixef.pharmacometrics.Param class method) positive_definite (pymixef.convergence.HessianDiagnostics attribute) (pymixef.covariance.CovarianceValidation attribute) (pymixef.HessianDiagnostics attribute) power (pymixef.pharmacometrics.CombinedError attribute) (pymixef.pharmacometrics.pk.CombinedError attribute) (pymixef.pharmacometrics.pk.PowerError attribute) (pymixef.pharmacometrics.PowerError attribute) power() (in module pymixef.pharmacometrics) (in module pymixef.pharmacometrics.pk) PowerError (class in pymixef.pharmacometrics) (class in pymixef.pharmacometrics.pk) predict (pymixef.pharmacometrics.ConditionalObjective attribute) (pymixef.pharmacometrics.estimation.ConditionalObjective attribute) prediction() (pymixef.FitResult method) (pymixef.results.FitResult method) predictions (pymixef.pharmacometrics.estimation.ObjectiveComponents attribute) (pymixef.pharmacometrics.ObjectiveComponents attribute) PredictorIR (class in pymixef.ir) predictors (pymixef.ir.ModelIR attribute) (pymixef.ModelIR attribute) prepare_data() (in module pymixef.backends.base) (in module pymixef.data) prepare_random_block() (in module pymixef.backends.base) PriorIR (class in pymixef.ir) priors (pymixef.ir.ModelIR attribute) (pymixef.Model attribute) (pymixef.model.Model attribute) (pymixef.ModelIR attribute) probabilities() (pymixef.families.Ordinal method) probit (pymixef.families.links attribute) proportional() (in module pymixef.pharmacometrics) (in module pymixef.pharmacometrics.pk) proportional_sigma (pymixef.pharmacometrics.CombinedError attribute) (pymixef.pharmacometrics.pk.CombinedError attribute) ProportionalError (class in pymixef.pharmacometrics) (class in pymixef.pharmacometrics.pk) proposal_scale (pymixef.pharmacometrics.estimation.SAEMControl attribute) (pymixef.pharmacometrics.SAEMControl attribute) proposals (pymixef.pharmacometrics.estimation.SAEMResult attribute) (pymixef.pharmacometrics.SAEMResult attribute) provenance() (pymixef.pharmacometrics.events.EventTable method) (pymixef.pharmacometrics.EventTable method) pymixef module pymixef.backends module pymixef.backends.base module pymixef.backends.glmm module pymixef.backends.lmm module pymixef.backends.mmrm module pymixef.capabilities module pymixef.cli module pymixef.compare module pymixef.convergence module pymixef.covariance module pymixef.data module pymixef.diagnostics module pymixef.errors module pymixef.families module pymixef.formula module pymixef.inference module pymixef.interoperability module pymixef.interoperability.base module pymixef.interoperability.nonmem module pymixef.interoperability.pharmml module pymixef.interoperability.r module pymixef.interoperability.sbml module pymixef.interoperability.sedml module pymixef.ir module pymixef.model module pymixef.native module pymixef.pharmacometrics module pymixef.pharmacometrics.dsl module pymixef.pharmacometrics.estimation module pymixef.pharmacometrics.events module pymixef.pharmacometrics.ode module pymixef.pharmacometrics.pk module pymixef.plugins module pymixef.provenance module pymixef.random module pymixef.reporting module pymixef.results module pymixef.transforms module pymixef.validation module pymixef.warnings module PyMixEFError, [1] PyMixEFWarning R raise_for_errors() (pymixef.model.ValidationReport method) (pymixef.pharmacometrics.dsl.ModelValidation method) (pymixef.pharmacometrics.ModelValidation method) Random (class in pymixef) (class in pymixef.model) random (pymixef.Model attribute) (pymixef.model.Model attribute) Random effect random() (pymixef.families.Family method) random_blocks (pymixef.backends.base.CompiledData attribute) (pymixef.formula.DesignMatrices attribute) (pymixef.formula.FormulaExplanation attribute) random_covariance() (in module pymixef.backends.base) random_design (pymixef.backends.base.CompiledData property) random_effect (pymixef.pharmacometrics.estimation.ObjectiveComponents attribute) (pymixef.pharmacometrics.ObjectiveComponents attribute) random_effect_objective (pymixef.pharmacometrics.ConditionalModeResult attribute) (pymixef.pharmacometrics.estimation.ConditionalModeResult attribute) random_effects (pymixef.FitResult attribute) (pymixef.ir.ModelIR attribute) (pymixef.ModelIR attribute) (pymixef.results.FitResult attribute) random_streams() (in module pymixef) (in module pymixef.random) random_terms (pymixef.formula.FormulaSpec attribute) RandomBlockData (class in pymixef.backends.base) RandomDesignBlock (class in pymixef.formula) RandomEffectIR (class in pymixef.ir) RandomStreamManager (class in pymixef) (class in pymixef.random) RandomTerm (class in pymixef.formula) rate (pymixef.pharmacometrics.CanonicalEvent attribute) RATE (pymixef.pharmacometrics.CanonicalEvent property) rate (pymixef.pharmacometrics.Dose attribute) (pymixef.pharmacometrics.dsl.Dose attribute) (pymixef.pharmacometrics.events.CanonicalEvent attribute) RATE (pymixef.pharmacometrics.events.CanonicalEvent property) real() (pymixef.pharmacometrics.dsl.Param class method) (pymixef.pharmacometrics.Param class method) reason_code (pymixef.data.AuditRecord attribute) reason_counts (pymixef.data.DataAudit property) RECORDED (pymixef.pharmacometrics.DoseAmountStatus attribute) (pymixef.pharmacometrics.events.DoseAmountStatus attribute) records (pymixef.data.DataAudit attribute) (pymixef.data.PatternMixtureResult attribute) (pymixef.PatternMixtureResult attribute) reference (pymixef.pharmacometrics.dsl.Symbol attribute) (pymixef.pharmacometrics.Symbol attribute) REFERENCE_VALIDATED (pymixef.Maturity attribute) register() (pymixef.plugins.Registry method) register_ir_migration() (in module pymixef.ir) Registry (class in pymixef.plugins) REGULATED_WORKFLOW_SUPPORT (pymixef.Maturity attribute) remediation (pymixef.WarningRecord attribute) REML render_report() (in module pymixef) (in module pymixef.reporting) replicates() (pymixef.random.RandomStreamManager method) (pymixef.RandomStreamManager method) report (pymixef.interoperability.base.InterchangeResult attribute) (pymixef.interoperability.InterchangeResult attribute) reproducibility (pymixef.capabilities.Capability attribute) (pymixef.validation.TraceabilityRecord attribute) Reproducibility class reproducibility_class (pymixef.pharmacometrics.estimation.SAEMResult attribute) (pymixef.pharmacometrics.SAEMResult attribute) (pymixef.provenance.RunManifest attribute) (pymixef.RunManifest attribute) ReproducibilityClass (class in pymixef) requested_groups (pymixef.diagnostics.GroupInfluenceResult attribute) (pymixef.GroupInfluenceResult attribute) require_supported() (pymixef.interoperability.base.CompatibilityReport method) (pymixef.interoperability.base.InterchangeResult method) (pymixef.interoperability.CompatibilityReport method) (pymixef.interoperability.InterchangeResult method) requirement (pymixef.validation.TraceabilityRecord attribute) RequirementLinks (class in pymixef.validation) resampling (pymixef.BootstrapResult attribute) (pymixef.inference.BootstrapResult attribute) RESET (pymixef.pharmacometrics.events.EventType attribute) (pymixef.pharmacometrics.EventType attribute) RESET_AND_DOSE (pymixef.pharmacometrics.events.EventType attribute) (pymixef.pharmacometrics.EventType attribute) Residual residual (pymixef.Model attribute) (pymixef.model.Model attribute) residual_covariance (pymixef.backends.base.CompiledData attribute) residual_covariance_fixed (pymixef.backends.base.CompiledData attribute) residual_diagnostics() (pymixef.FitResult method) (pymixef.results.FitResult method) residual_table() (in module pymixef.diagnostics) residuals (pymixef.FitResult attribute) (pymixef.results.FitResult attribute) Response (class in pymixef) (class in pymixef.model) response (pymixef.data.PatternMixtureResult attribute) (pymixef.formula.DesignMatrices attribute) (pymixef.formula.FormulaExplanation attribute) (pymixef.formula.FormulaSpec attribute) (pymixef.ir.LikelihoodIR attribute) (pymixef.ir.ModelIR attribute) (pymixef.Model attribute) (pymixef.model.Model attribute) (pymixef.ModelIR attribute) (pymixef.PatternMixtureResult attribute) result_schema_version (pymixef.FitResult attribute) (pymixef.results.FitResult attribute) retained_positions (pymixef.data.AuditedData attribute) rhs (pymixef.ir.StateEquationIR attribute) right_censored_loglikelihood() (in module pymixef.pharmacometrics) (in module pymixef.pharmacometrics.pk) role (pymixef.data.ColumnSchema attribute) (pymixef.ir.ParameterIR attribute) (pymixef.pharmacometrics.dsl.Symbol attribute) (pymixef.pharmacometrics.Symbol attribute) route (pymixef.pharmacometrics.Dose attribute) (pymixef.pharmacometrics.dsl.Dose attribute) row_design (pymixef.backends.base.RandomBlockData attribute) row_id (pymixef.data.AuditRecord attribute) (pymixef.data.PatternMixtureRecord attribute) (pymixef.pharmacometrics.AuditEntry attribute) (pymixef.pharmacometrics.CanonicalEvent attribute) (pymixef.pharmacometrics.events.AuditEntry attribute) (pymixef.pharmacometrics.events.CanonicalEvent attribute) (pymixef.pharmacometrics.EventSnapshot attribute) (pymixef.pharmacometrics.ode.EventSnapshot attribute) row_ids (pymixef.data.AuditedData property) (pymixef.data.ColumnarData attribute) (pymixef.formula.DesignMatrices attribute) rtol (pymixef.pharmacometrics.ode.ODESolverMetadata attribute) (pymixef.pharmacometrics.ODESolverMetadata attribute) RunManifest (class in pymixef) (class in pymixef.provenance) RunTimer (class in pymixef.provenance) rvs() (pymixef.families.Bernoulli method) (pymixef.families.Beta method) (pymixef.families.Binomial method) (pymixef.families.Censored method) (pymixef.families.COMPoisson method) (pymixef.families.Exponential method) (pymixef.families.Family method) (pymixef.families.Gamma method) (pymixef.families.Gaussian method) (pymixef.families.GeneralizedPoisson method) (pymixef.families.Gompertz method) (pymixef.families.Hurdle method) (pymixef.families.InverseGaussian method) (pymixef.families.LogLogistic method) (pymixef.families.LogNormal method) (pymixef.families.LogNormalSurvival method) (pymixef.families.Multinomial method) (pymixef.families.NegativeBinomial2 method) (pymixef.families.Ordinal method) (pymixef.families.PiecewiseExponential method) (pymixef.families.Poisson method) (pymixef.families.StudentT method) (pymixef.families.Truncated method) (pymixef.families.Tweedie method) (pymixef.families.Weibull method) (pymixef.families.ZeroInflated method) S SAEM saem() (in module pymixef.pharmacometrics) (in module pymixef.pharmacometrics.estimation) SAEMControl (class in pymixef.pharmacometrics) (class in pymixef.pharmacometrics.estimation) SAEMError, [1] SAEMProblem (class in pymixef.pharmacometrics) (class in pymixef.pharmacometrics.estimation) SAEMResult (class in pymixef.pharmacometrics) (class in pymixef.pharmacometrics.estimation) safe_cholesky() (in module pymixef.backends.base) same_time_order (pymixef.pharmacometrics.ode.ODESolverMetadata attribute) (pymixef.pharmacometrics.ODESolverMetadata attribute) save() (pymixef.diagnostics.DiagnosticTable method) (pymixef.FitResult method) (pymixef.results.FitResult method) scaled_gradient_inf_norm (pymixef.convergence.ConvergenceReport attribute) (pymixef.ConvergenceReport attribute) schema (pymixef.data.ColumnarData attribute) schema_version (pymixef.ir.ModelIR attribute) (pymixef.ModelIR attribute) (pymixef.pharmacometrics.CompiledModel attribute) (pymixef.pharmacometrics.dsl.CompiledModel attribute) scipy_version (pymixef.pharmacometrics.ode.ODESolverMetadata attribute) (pymixef.pharmacometrics.ODESolverMetadata attribute) seed (pymixef.BootstrapResult attribute) (pymixef.inference.BootstrapResult attribute) (pymixef.pharmacometrics.estimation.SAEMControl attribute) (pymixef.pharmacometrics.estimation.SAEMResult attribute) (pymixef.pharmacometrics.SAEMControl attribute) (pymixef.pharmacometrics.SAEMResult attribute) (pymixef.random.RandomStreamManager attribute) (pymixef.RandomStreamManager attribute) seeds (pymixef.provenance.RunManifest attribute) (pymixef.RunManifest attribute) segments (pymixef.pharmacometrics.ode.ODESolverMetadata attribute) (pymixef.pharmacometrics.ODESolverMetadata attribute) select_optimizer_result() (in module pymixef.backends.base) Semantic hash semantic_hash (pymixef.ir.ModelIR property) (pymixef.ModelIR property) semantically_equal() (pymixef.ir.ModelIR method) (pymixef.ModelIR method) sensitivities (pymixef.pharmacometrics.ode.ODESimulationResult attribute) (pymixef.pharmacometrics.ODESimulationResult attribute) sensitivity() (pymixef.pharmacometrics.ode.ODESimulationResult method) (pymixef.pharmacometrics.ODESimulationResult method) sensitivity_method (pymixef.pharmacometrics.ode.ODESolverMetadata attribute) (pymixef.pharmacometrics.ODESolverMetadata attribute) sensitivity_parameters (pymixef.pharmacometrics.ode.ODESimulationResult attribute) (pymixef.pharmacometrics.ODESimulationResult attribute) sensitivity_step (pymixef.pharmacometrics.ode.ODESolverMetadata attribute) (pymixef.pharmacometrics.ODESolverMetadata attribute) SensitivityCheck (class in pymixef.pharmacometrics) (class in pymixef.pharmacometrics.ode) settings (pymixef.ApproximationSensitivityResult attribute) (pymixef.compare.ApproximationSensitivityResult attribute) (pymixef.ExecutionPlan attribute) (pymixef.model.ExecutionPlan attribute) (pymixef.provenance.RunManifest attribute) (pymixef.RunManifest attribute) severity (pymixef.model.ValidationFinding attribute) (pymixef.pharmacometrics.dsl.ValidationMessage attribute) (pymixef.pharmacometrics.ValidationMessage attribute) (pymixef.WarningRecord attribute) sf() (pymixef.families.Family method) shape (pymixef.Model attribute) (pymixef.model.Model attribute) sigma (pymixef.pharmacometrics.AdditiveError attribute) (pymixef.pharmacometrics.LogNormalError attribute) (pymixef.pharmacometrics.pk.AdditiveError attribute) (pymixef.pharmacometrics.pk.LogNormalError attribute) (pymixef.pharmacometrics.pk.PowerError attribute) (pymixef.pharmacometrics.pk.ProportionalError attribute) (pymixef.pharmacometrics.PowerError attribute) (pymixef.pharmacometrics.ProportionalError attribute) SimplexTransform (class in pymixef.transforms) simulate() (pymixef.covariance.CovarianceStructure method) (pymixef.families.Family method) (pymixef.FitResult method) (pymixef.pharmacometrics.LogNormalError method) (pymixef.pharmacometrics.pk.LogNormalError method) (pymixef.plugins.CovariancePlugin method) (pymixef.results.FitResult method) simulate_ode() (in module pymixef.pharmacometrics) (in module pymixef.pharmacometrics.ode) simulate_subjects() (in module pymixef.pharmacometrics) (in module pymixef.pharmacometrics.ode) singularity_report() (in module pymixef.covariance) size (pymixef.backends.base.CovarianceParameterization property) snapshot() (pymixef.plugins.Registry method) SoftplusTransform (class in pymixef.transforms) solver (pymixef.pharmacometrics.ode.ODESolverMetadata attribute) (pymixef.pharmacometrics.ODESolverMetadata attribute) source (pymixef.backends.base.CompiledData attribute) (pymixef.data.AuditedData attribute) (pymixef.formula.FormulaSpec attribute) (pymixef.formula.RandomTerm attribute) (pymixef.ir.ModelIR attribute) (pymixef.ModelIR attribute) (pymixef.plugins.PluginInfo attribute) (pymixef.provenance.RunManifest attribute) (pymixef.RunManifest attribute) Source row source_count (pymixef.pharmacometrics.events.EventTable attribute) (pymixef.pharmacometrics.EventTable attribute) source_data (pymixef.ExecutionPlan attribute) (pymixef.model.ExecutionPlan attribute) source_events (pymixef.pharmacometrics.ode.ODESolverMetadata attribute) (pymixef.pharmacometrics.ODESolverMetadata attribute) source_files (pymixef.validation.RequirementLinks attribute) (pymixef.validation.TraceabilityRecord attribute) source_fingerprint (pymixef.data.DataAudit attribute) (pymixef.data.PatternMixtureResult attribute) (pymixef.PatternMixtureResult attribute) source_format (pymixef.interoperability.base.CompatibilityReport attribute) (pymixef.interoperability.CompatibilityReport attribute) source_index (pymixef.data.AuditRecord attribute) (pymixef.data.ColumnarData attribute) (pymixef.data.PatternMixtureRecord attribute) source_location (pymixef.ir.IRNode attribute) source_position (pymixef.pharmacometrics.CanonicalEvent attribute) (pymixef.pharmacometrics.events.CanonicalEvent attribute) source_records (pymixef.pharmacometrics.events.EventTable attribute) (pymixef.pharmacometrics.EventTable attribute) source_row_id (pymixef.pharmacometrics.AuditEntry attribute) (pymixef.pharmacometrics.CanonicalEvent attribute) (pymixef.pharmacometrics.events.AuditEntry attribute) (pymixef.pharmacometrics.events.CanonicalEvent attribute) (pymixef.pharmacometrics.EventSnapshot attribute) (pymixef.pharmacometrics.ode.EventSnapshot attribute) source_type (pymixef.data.ColumnarData attribute) SpatialPower (class in pymixef.covariance) SpatialPowerCovariance (in module pymixef.covariance) spec (pymixef.formula.DesignMatrices attribute) specification (pymixef.Model property) (pymixef.model.Model property) specification_files (pymixef.validation.RequirementLinks attribute) (pymixef.validation.TraceabilityRecord attribute) sqrt() (in module pymixef.pharmacometrics) (in module pymixef.pharmacometrics.dsl) SS (pymixef.pharmacometrics.CanonicalEvent property) ss (pymixef.pharmacometrics.CanonicalEvent property) SS (pymixef.pharmacometrics.events.CanonicalEvent property) ss (pymixef.pharmacometrics.events.CanonicalEvent property) STABLE (pymixef.Maturity attribute) stable_sort() (in module pymixef.data) stage (pymixef.capabilities.Capability attribute) (pymixef.validation.TraceabilityRecord attribute) State (class in pymixef.pharmacometrics) (class in pymixef.pharmacometrics.dsl) state (pymixef.ir.StateEquationIR attribute) (pymixef.pharmacometrics.DifferentialEquation attribute) (pymixef.pharmacometrics.Dose attribute) (pymixef.pharmacometrics.dsl.DifferentialEquation attribute) (pymixef.pharmacometrics.dsl.Dose attribute) (pymixef.pharmacometrics.EventSnapshot attribute) (pymixef.pharmacometrics.ode.EventSnapshot attribute) state() (pymixef.pharmacometrics.ode.ODESimulationResult method) (pymixef.pharmacometrics.ODESimulationResult method) state_equations (pymixef.ir.ModelIR attribute) (pymixef.ModelIR attribute) state_names (pymixef.pharmacometrics.ode.ODESimulationResult attribute) (pymixef.pharmacometrics.ODESimulationResult attribute) StateEquationIR (class in pymixef.ir) states (pymixef.pharmacometrics.CompiledModel attribute) (pymixef.pharmacometrics.dsl.CompiledModel attribute) (pymixef.pharmacometrics.ode.ODESimulationResult attribute) (pymixef.pharmacometrics.ODESimulationResult attribute) status (pymixef.convergence.ConvergenceReport attribute) (pymixef.ConvergenceReport attribute) steady_state (pymixef.pharmacometrics.CanonicalEvent attribute) (pymixef.pharmacometrics.events.CanonicalEvent attribute) step (pymixef.pharmacometrics.ode.SensitivityCheck attribute) (pymixef.pharmacometrics.SensitivityCheck attribute) step_exponent (pymixef.pharmacometrics.estimation.SAEMControl attribute) (pymixef.pharmacometrics.estimation.SAEMResult attribute) (pymixef.pharmacometrics.SAEMControl attribute) (pymixef.pharmacometrics.SAEMResult attribute) step_sizes (pymixef.pharmacometrics.estimation.SAEMResult attribute) (pymixef.pharmacometrics.SAEMResult attribute) STOCHASTIC_MONTE_CARLO (pymixef.ReproducibilityClass attribute) stratified_by (pymixef.data.PatternMixtureResult attribute) (pymixef.PatternMixtureResult attribute) stratum (pymixef.data.PatternMixtureRecord attribute) STRUCTURALLY_ABSENT_ENDPOINT (pymixef.data.MissingnessKind attribute) structure (pymixef.ir.CovarianceIR attribute) Student (in module pymixef.families) StudentT (class in pymixef.families) subject_contributions (pymixef.pharmacometrics.estimation.LaplacePopulationResult attribute) (pymixef.pharmacometrics.LaplacePopulationResult attribute) subject_id (pymixef.pharmacometrics.CanonicalEvent attribute) (pymixef.pharmacometrics.events.CanonicalEvent attribute) (pymixef.pharmacometrics.EventSnapshot attribute) (pymixef.pharmacometrics.ode.EventSnapshot attribute) (pymixef.pharmacometrics.ode.ODEContext attribute) (pymixef.pharmacometrics.ode.ODESimulationResult attribute) (pymixef.pharmacometrics.ODEContext attribute) (pymixef.pharmacometrics.ODESimulationResult attribute) subjects (pymixef.pharmacometrics.events.EventTable property) (pymixef.pharmacometrics.EventTable property) success (pymixef.FitResult property) (pymixef.pharmacometrics.ConditionalModeResult attribute) (pymixef.pharmacometrics.estimation.ConditionalModeResult attribute) (pymixef.pharmacometrics.ode.ODESolverMetadata attribute) (pymixef.pharmacometrics.ODESolverMetadata attribute) (pymixef.results.FitResult property) successful_groups (pymixef.diagnostics.GroupInfluenceResult property) (pymixef.GroupInfluenceResult property) successful_replicates (pymixef.BootstrapResult property) (pymixef.inference.BootstrapResult property) successful_scenarios (pymixef.ApproximationSensitivityResult property) (pymixef.compare.ApproximationSensitivityResult property) sufficient_statistics (pymixef.pharmacometrics.estimation.SAEMProblem attribute) (pymixef.pharmacometrics.estimation.SAEMResult attribute) (pymixef.pharmacometrics.SAEMProblem attribute) (pymixef.pharmacometrics.SAEMResult attribute) suggested_engines (pymixef.model.ValidationFinding attribute) summary() (pymixef.FitResult method) (pymixef.results.FitResult method) support (pymixef.families.Bernoulli attribute) (pymixef.families.Beta attribute) (pymixef.families.Binomial attribute) (pymixef.families.COMPoisson attribute) (pymixef.families.Family attribute) (pymixef.families.Gamma attribute) (pymixef.families.Gaussian attribute) (pymixef.families.GeneralizedPoisson attribute) (pymixef.families.InverseGaussian attribute) (pymixef.families.LogNormal attribute) (pymixef.families.Multinomial attribute) (pymixef.families.NegativeBinomial2 attribute) (pymixef.families.Ordinal attribute) (pymixef.families.Poisson attribute) (pymixef.families.StudentT attribute) (pymixef.families.Tweedie attribute) (pymixef.ir.IRNode attribute) supported (pymixef.interoperability.base.CompatibilityReport property) (pymixef.interoperability.CompatibilityReport property) Symbol (class in pymixef.pharmacometrics) (class in pymixef.pharmacometrics.dsl) symbol() (in module pymixef.pharmacometrics) (in module pymixef.pharmacometrics.dsl) symbols (pymixef.pharmacometrics.CompiledModel attribute) (pymixef.pharmacometrics.dsl.CompiledModel attribute) symmetric (pymixef.covariance.CovarianceValidation attribute) T table (pymixef.ApproximationSensitivityResult attribute) (pymixef.compare.ApproximationSensitivityResult attribute) (pymixef.compare.ComparisonResult attribute) (pymixef.ComparisonResult attribute) (pymixef.diagnostics.GroupInfluenceResult attribute) (pymixef.GroupInfluenceResult attribute) take() (pymixef.data.ColumnarData method) target (pymixef.ir.CovarianceIR attribute) (pymixef.ir.EventIR attribute) (pymixef.ir.PriorIR attribute) target_format (pymixef.interoperability.base.CompatibilityReport attribute) (pymixef.interoperability.CompatibilityReport attribute) term_names (pymixef.backends.base.RandomBlockData attribute) (pymixef.formula.RandomDesignBlock attribute) (pymixef.formula.RandomTerm property) terms (pymixef.formula.RandomTerm attribute) (pymixef.ir.RandomEffectIR attribute) terms_per_group (pymixef.backends.base.RandomBlockData attribute) tests (pymixef.validation.TraceabilityRecord attribute) time (pymixef.pharmacometrics.CanonicalEvent attribute) TIME (pymixef.pharmacometrics.CanonicalEvent property) time (pymixef.pharmacometrics.events.CanonicalEvent attribute) TIME (pymixef.pharmacometrics.events.CanonicalEvent property) time (pymixef.pharmacometrics.EventSnapshot attribute) (pymixef.pharmacometrics.ode.EventSnapshot attribute) times (pymixef.pharmacometrics.ode.ODESimulationResult attribute) (pymixef.pharmacometrics.ODESimulationResult attribute) to_backend_data() (pymixef.ExecutionPlan method) (pymixef.formula.DesignMatrices method) (pymixef.model.ExecutionPlan method) to_dict() (pymixef.ApproximationSensitivityResult method) (pymixef.backends.BackendError method) (pymixef.backends.BackendUnsupportedError method) (pymixef.backends.base.BackendError method) (pymixef.backends.base.BackendUnsupportedError method) (pymixef.BootstrapResult method) (pymixef.BoundaryRecord method) (pymixef.capabilities.Capability method) (pymixef.compare.ApproximationSensitivityResult method) (pymixef.compare.ComparisonResult method) (pymixef.ComparisonResult method) (pymixef.convergence.BoundaryRecord method) (pymixef.convergence.ConvergenceReport method) (pymixef.convergence.HessianDiagnostics method) (pymixef.ConvergenceReport method) (pymixef.covariance.CovarianceStructure method) (pymixef.covariance.CovarianceValidation method) (pymixef.data.AuditRecord method) (pymixef.data.ColumnarData method) (pymixef.data.ColumnSchema method) (pymixef.data.DataAudit method) (pymixef.data.PatternMixtureRecord method) (pymixef.data.PatternMixtureResult method) (pymixef.diagnostics.DiagnosticTable method) (pymixef.diagnostics.GroupInfluenceResult method) (pymixef.EngineCompatibilityError method) (pymixef.errors.EngineCompatibilityError method) (pymixef.errors.PyMixEFError method) (pymixef.FitResult method) (pymixef.formula.FormulaExplanation method) (pymixef.formula.FormulaSpec method) (pymixef.formula.RandomDesignBlock method) (pymixef.formula.RandomTerm method) (pymixef.GroupInfluenceResult method) (pymixef.HessianDiagnostics method) (pymixef.inference.BootstrapResult method) (pymixef.interoperability.base.CompatibilityReport method) (pymixef.interoperability.CompatibilityReport method) (pymixef.ir.DiffEntry method) (pymixef.ir.IRNode method) (pymixef.ir.ModelDiff method) (pymixef.ir.ModelIR method) (pymixef.model.ValidationFinding method) (pymixef.model.ValidationReport method) (pymixef.ModelIR method) (pymixef.PatternMixtureResult method) (pymixef.pharmacometrics.AdditiveError method) (pymixef.pharmacometrics.AuditEntry method) (pymixef.pharmacometrics.CombinedError method) (pymixef.pharmacometrics.CompiledModel method) (pymixef.pharmacometrics.DifferentialEquation method) (pymixef.pharmacometrics.Dose method) (pymixef.pharmacometrics.dsl.CompiledModel method) (pymixef.pharmacometrics.dsl.DifferentialEquation method) (pymixef.pharmacometrics.dsl.Dose method) (pymixef.pharmacometrics.dsl.Eta method) (pymixef.pharmacometrics.dsl.Expr method) (pymixef.pharmacometrics.dsl.ModelDefinition method) (pymixef.pharmacometrics.dsl.ModelValidation method) (pymixef.pharmacometrics.dsl.Observation method) (pymixef.pharmacometrics.dsl.Param method) (pymixef.pharmacometrics.dsl.State method) (pymixef.pharmacometrics.dsl.Symbol method) (pymixef.pharmacometrics.dsl.ValidationMessage method) (pymixef.pharmacometrics.estimation.SAEMResult method) (pymixef.pharmacometrics.Eta method) (pymixef.pharmacometrics.events.AuditEntry method) (pymixef.pharmacometrics.Expr method) (pymixef.pharmacometrics.LogNormalError method) (pymixef.pharmacometrics.ModelDefinition method) (pymixef.pharmacometrics.ModelValidation method) (pymixef.pharmacometrics.Observation method) (pymixef.pharmacometrics.ObservationError method) (pymixef.pharmacometrics.ode.ODESimulationError method) (pymixef.pharmacometrics.ode.ODESolverMetadata method) (pymixef.pharmacometrics.ODESimulationError method) (pymixef.pharmacometrics.ODESolverMetadata method) (pymixef.pharmacometrics.Param method) (pymixef.pharmacometrics.pk.AdditiveError method) (pymixef.pharmacometrics.pk.CombinedError method) (pymixef.pharmacometrics.pk.LogNormalError method) (pymixef.pharmacometrics.pk.ObservationError method) (pymixef.pharmacometrics.pk.PowerError method) (pymixef.pharmacometrics.pk.ProportionalError method) (pymixef.pharmacometrics.PowerError method) (pymixef.pharmacometrics.ProportionalError method) (pymixef.pharmacometrics.SAEMResult method) (pymixef.pharmacometrics.State method) (pymixef.pharmacometrics.Symbol method) (pymixef.pharmacometrics.ValidationMessage method) (pymixef.provenance.RunManifest method) (pymixef.PyMixEFError method) (pymixef.random.RandomStreamManager method) (pymixef.RandomStreamManager method) (pymixef.results.FitResult method) (pymixef.RunManifest method) (pymixef.validation.TraceabilityRecord method) (pymixef.WarningRecord method) to_ir() (pymixef.formula.FormulaSpec method) (pymixef.Model method) (pymixef.model.Model method) (pymixef.pharmacometrics.CompiledModel method) (pymixef.pharmacometrics.dsl.CompiledModel method) (pymixef.pharmacometrics.dsl.ModelDefinition method) (pymixef.pharmacometrics.ModelDefinition method) to_json() (pymixef.ir.ModelDiff method) (pymixef.ir.ModelIR method) (pymixef.ModelIR method) to_record() (pymixef.pharmacometrics.CanonicalEvent method) (pymixef.pharmacometrics.events.CanonicalEvent method) to_records() (pymixef.pharmacometrics.events.EventTable method) (pymixef.pharmacometrics.EventTable method) to_source_records() (pymixef.pharmacometrics.events.EventTable method) (pymixef.pharmacometrics.EventTable method) Toeplitz (class in pymixef.covariance) ToeplitzCovariance (in module pymixef.covariance) tolerance (pymixef.BoundaryRecord attribute) (pymixef.convergence.BoundaryRecord attribute) total (pymixef.pharmacometrics.estimation.ObjectiveComponents attribute) (pymixef.pharmacometrics.ObjectiveComponents attribute) traceability_matrix() (in module pymixef) (in module pymixef.validation) TraceabilityRecord (class in pymixef.validation) Transform (class in pymixef.transforms) transform (pymixef.ir.IRNode attribute) transformations (pymixef.data.DataAudit attribute) TransformError TransformIR (class in pymixef.ir) transforms (pymixef.ir.ModelIR attribute) (pymixef.ModelIR attribute) translate_r_formula() (in module pymixef.interoperability) (in module pymixef.interoperability.r) trials (pymixef.backends.base.CompiledData attribute) Truncated (class in pymixef.families) TruncatedFamily (in module pymixef.families) trustworthy (pymixef.convergence.ConvergenceReport property) (pymixef.ConvergenceReport property) Trustworthy convergence Tweedie (class in pymixef.families) two_compartment_bolus() (in module pymixef.pharmacometrics) (in module pymixef.pharmacometrics.pk) two_compartment_infusion() (in module pymixef.pharmacometrics) (in module pymixef.pharmacometrics.pk) two_compartment_iv_bolus() (in module pymixef.pharmacometrics) (in module pymixef.pharmacometrics.pk) two_compartment_iv_infusion() (in module pymixef.pharmacometrics) (in module pymixef.pharmacometrics.pk) two_compartment_oral() (in module pymixef.pharmacometrics) (in module pymixef.pharmacometrics.pk) two_compartment_rates() (in module pymixef.pharmacometrics) (in module pymixef.pharmacometrics.pk) TwoCompartmentPK (class in pymixef.pharmacometrics) (class in pymixef.pharmacometrics.pk) TwoCompartmentRates (class in pymixef.pharmacometrics) (class in pymixef.pharmacometrics.pk) U unconstrained_names() (pymixef.backends.base.CovarianceParameterization method) unconstrained_parameters (pymixef.FitResult attribute) (pymixef.results.FitResult attribute) unconstrained_size (pymixef.transforms.CholeskyCovarianceTransform property) unit (pymixef.data.ColumnSchema attribute) (pymixef.ir.IRNode attribute) (pymixef.model.Response attribute) (pymixef.pharmacometrics.dsl.Param attribute) (pymixef.pharmacometrics.dsl.State attribute) (pymixef.pharmacometrics.dsl.Symbol attribute) (pymixef.pharmacometrics.Param attribute) (pymixef.pharmacometrics.State attribute) (pymixef.pharmacometrics.Symbol attribute) (pymixef.Response attribute) UNKNOWN (pymixef.pharmacometrics.DoseAmountStatus attribute) (pymixef.pharmacometrics.events.DoseAmountStatus attribute) unregister() (pymixef.plugins.Registry method) Unstructured (class in pymixef.covariance) UnstructuredCovariance (in module pymixef.covariance) UnsupportedCapabilityError, [1] UnsupportedEngineError (in module pymixef.errors) UnsupportedEstimatorError, [1] UnsupportedEventSemantics, [1] upper (pymixef.pharmacometrics.dsl.Param attribute) (pymixef.pharmacometrics.Param attribute) (pymixef.transforms.BoundedTransform attribute) V valid (pymixef.model.ValidationReport property) (pymixef.pharmacometrics.dsl.ModelValidation attribute) (pymixef.pharmacometrics.ModelValidation attribute) validate() (pymixef.covariance.CovarianceStructure method) (pymixef.ExecutionPlan method) (pymixef.Model method) (pymixef.model.ExecutionPlan method) (pymixef.model.Model method) (pymixef.pharmacometrics.CompiledModel method) (pymixef.pharmacometrics.dsl.CompiledModel method) (pymixef.pharmacometrics.dsl.ModelDefinition method) (pymixef.pharmacometrics.ModelDefinition method) (pymixef.plugins.CovariancePlugin method) validate_covariance() (in module pymixef.covariance) validate_monotonic_time() (in module pymixef.data) validate_payload() (in module pymixef.backends) (in module pymixef.backends.base) validation (pymixef.ExecutionPlan attribute) (pymixef.model.ExecutionPlan attribute) Validation bundle ValidationError, [1] ValidationFinding (class in pymixef.model) ValidationMessage (class in pymixef.pharmacometrics) (class in pymixef.pharmacometrics.dsl) ValidationReport (class in pymixef.model) value (pymixef.BoundaryRecord attribute) (pymixef.convergence.BoundaryRecord attribute) (pymixef.interoperability.base.InterchangeResult attribute) (pymixef.interoperability.InterchangeResult attribute) (pymixef.pharmacometrics.dsl.Expr attribute) (pymixef.pharmacometrics.Expr attribute) variance() (pymixef.families.Bernoulli method) (pymixef.families.Beta method) (pymixef.families.Binomial method) (pymixef.families.COMPoisson method) (pymixef.families.Exponential method) (pymixef.families.Family method) (pymixef.families.Gamma method) (pymixef.families.Gaussian method) (pymixef.families.GeneralizedPoisson method) (pymixef.families.Gompertz method) (pymixef.families.Hurdle method) (pymixef.families.InverseGaussian method) (pymixef.families.LogLogistic method) (pymixef.families.LogNormal method) (pymixef.families.LogNormalSurvival method) (pymixef.families.Multinomial method) (pymixef.families.NegativeBinomial1 method) (pymixef.families.NegativeBinomial2 method) (pymixef.families.Ordinal method) (pymixef.families.PiecewiseExponential method) (pymixef.families.Poisson method) (pymixef.families.StudentT method) (pymixef.families.Tweedie method) (pymixef.families.Weibull method) (pymixef.families.ZeroInflated method) (pymixef.pharmacometrics.AdditiveError method) (pymixef.pharmacometrics.CombinedError method) (pymixef.pharmacometrics.LogNormalError method) (pymixef.pharmacometrics.ObservationError method) (pymixef.pharmacometrics.pk.AdditiveError method) (pymixef.pharmacometrics.pk.CombinedError method) (pymixef.pharmacometrics.pk.LogNormalError method) (pymixef.pharmacometrics.pk.ObservationError method) (pymixef.pharmacometrics.pk.PowerError method) (pymixef.pharmacometrics.pk.ProportionalError method) (pymixef.pharmacometrics.PowerError method) (pymixef.pharmacometrics.ProportionalError method) variance_floor (pymixef.pharmacometrics.AdditiveError attribute) (pymixef.pharmacometrics.CombinedError attribute) (pymixef.pharmacometrics.pk.AdditiveError attribute) (pymixef.pharmacometrics.pk.CombinedError attribute) (pymixef.pharmacometrics.pk.PowerError attribute) (pymixef.pharmacometrics.pk.ProportionalError attribute) (pymixef.pharmacometrics.PowerError attribute) (pymixef.pharmacometrics.ProportionalError attribute) variances (pymixef.pharmacometrics.estimation.ObjectiveComponents attribute) (pymixef.pharmacometrics.ObjectiveComponents attribute) verify_validation_bundle() (in module pymixef) (in module pymixef.validation) version (pymixef.plugins.PluginInfo attribute) Visual predictive check (VPC) volume (pymixef.pharmacometrics.OneCompartmentPK attribute) (pymixef.pharmacometrics.pk.OneCompartmentPK attribute) vpc() (pymixef.FitResult method) (pymixef.results.FitResult method) vpc_table() (in module pymixef.diagnostics) W warning_codes (pymixef.pharmacometrics.ConditionalModeResult attribute) (pymixef.pharmacometrics.estimation.ConditionalModeResult attribute) (pymixef.pharmacometrics.estimation.LaplacePopulationResult attribute) (pymixef.pharmacometrics.estimation.SAEMResult attribute) (pymixef.pharmacometrics.LaplacePopulationResult attribute) (pymixef.pharmacometrics.SAEMResult attribute) warning_record() (in module pymixef.warnings) WarningRecord (class in pymixef) warnings (pymixef.convergence.ConvergenceReport attribute) (pymixef.ConvergenceReport attribute) (pymixef.FitResult attribute) (pymixef.provenance.RunManifest attribute) (pymixef.results.FitResult attribute) (pymixef.RunManifest attribute) Weibull (class in pymixef.families) WeibullSurvival (in module pymixef.families) weights (pymixef.backends.base.CompiledData attribute) with_outputs() (pymixef.provenance.RunManifest method) (pymixef.RunManifest method) write() (pymixef.interoperability.base.CompatibilityReport method) (pymixef.interoperability.CompatibilityReport method) write_report() (pymixef.compare.ComparisonResult method) (pymixef.ComparisonResult method) X X (pymixef.backends.base.CompiledData attribute) (pymixef.formula.DesignMatrices property) Y y (pymixef.backends.base.CompiledData attribute) (pymixef.formula.DesignMatrices property) Z Z (pymixef.formula.RandomDesignBlock property) zero_inflation (pymixef.Model attribute) (pymixef.model.Model attribute) ZeroInflated (class in pymixef.families) ZeroInflatedFamily (in module pymixef.families)
