Index

A

AbstractAlgo (class in leaspy.algo.abstract_algo), [1] AbstractAttributes (class in leaspy.models.utils.attributes.abstract_attributes), [1] AbstractFitAlgo (class in leaspy.algo.fit.abstract_fit_algo), [1] AbstractFitMCMC (class in leaspy.algo.fit.abstract_mcmc), [1] AbstractGaussianNoiseModel (class in leaspy.models.noise_models), [1] (class in leaspy.models.noise_models.gaussian) AbstractIndividualSampler (class in leaspy.samplers), [1] (class in leaspy.samplers.base) AbstractManifoldModelAttributes (class in leaspy.models.utils.attributes.abstract_manifold_model_attributes), [1] AbstractMCMCPersonalizeAlgo (class in leaspy.algo.personalize.abstract_mcmc_personalize) AbstractModel (class in leaspy.models), [1] (class in leaspy.models.abstract_model) AbstractMultivariateModel (class in leaspy.models), [1] (class in leaspy.models.abstract_multivariate_model) AbstractOrdinalNoiseModel (class in leaspy.models.noise_models), [1] (class in leaspy.models.noise_models.ordinal) AbstractPersonalizeAlgo (class in leaspy.algo.personalize.abstract_personalize_algo), [1] AbstractPopulationGibbsSampler (class in leaspy.samplers.gibbs) AbstractPopulationSampler (class in leaspy.samplers), [1] (class in leaspy.samplers.base) AbstractRealization (class in leaspy.io.realizations), [1] (class in leaspy.io.realizations.realization) AbstractSampler (class in leaspy.samplers), [1] (class in leaspy.samplers.base) add_cofactors() (IndividualData method) add_individual_parameters() (IndividualParameters method), [1]

add_observations() (IndividualData method) algo() (AlgoFactory class method), [1] algo_class (AlgorithmSettings property), [1] AlgoFactory (class in leaspy.algo.algo_factory), [1] AlgorithmSettings (class in leaspy.io.settings.algorithm_settings), [1] AlgoWithAnnealingMixin (class in leaspy.algo.utils.algo_with_annealing) AlgoWithDeviceMixin (class in leaspy.algo.utils.algo_with_device) AlgoWithSamplersMixin (class in leaspy.algo.utils.algo_with_samplers) annealing_on (MeanReal attribute) (ModeReal attribute) (TensorMCMCSAEM attribute) API arg_constraints (MultinomialDistribution attribute) args (LeaspyAlgoInputError attribute) (LeaspyConvergenceError attribute) (LeaspyDataInputError attribute) (LeaspyException attribute) (LeaspyIndividualParamsInputError attribute) (LeaspyInputError attribute) (LeaspyModelInputError attribute) (LeaspyTypeError attribute) attachment attributes (MultivariateModel attribute) (UnivariateModel attribute), [1] attributes() (AttributesFactory class method), [1] AttributesFactory (class in leaspy.models.utils.attributes.attributes_factory), [1] average_trajectory() (Plotting method)

B

BaseModel (class in leaspy.models), [1] (class in leaspy.models.base) BaseNoiseModel (class in leaspy.models.noise_models), [1] (class in leaspy.models.noise_models.base)

batch_shape (MultinomialDistribution property) BernoulliFamily (class in leaspy.models.noise_models.bernoulli) BernoulliNoiseModel (class in leaspy.models.noise_models), [1] (class in leaspy.models.noise_models.bernoulli) biomarker

C

calibrate() (Leaspy method), [1] calibration canonical_loss_properties (AbstractGaussianNoiseModel attribute), [1] (AbstractOrdinalNoiseModel attribute), [1] (BaseNoiseModel attribute), [1] (BernoulliNoiseModel attribute), [1] (GaussianDiagonalNoiseModel attribute), [1] (GaussianScalarNoiseModel attribute), [1] (OrdinalNoiseModel attribute), [1] (OrdinalRankingNoiseModel attribute), [1] cdf() (MultinomialDistribution method) check_consistency() (AlgorithmSettings method), [1] check_if_initialized() (Leaspy method), [1] check_noise_model_compatibility() (AbstractModel method), [1], [2] (AbstractMultivariateModel method), [1], [2] (MultivariateModel method), [1], [2] (MultivariateParallelModel method), [1], [2] (OrdinalModelMixin method) (UnivariateModel method), [1], [2] clone() (CollectionRealization method), [1], [2] (DictRealizations method), [1], [2] cofactors (Data property), [1] CollectionRealization (class in leaspy.io.realizations), [1] (class in leaspy.io.realizations.collection_realization) colors() (Plotting method) compute_appropriate_ordinal_model() (AbstractMultivariateModel method), [1], [2] (MultivariateModel method), [1], [2] (MultivariateParallelModel method), [1], [2] (OrdinalModelMixin method) (UnivariateModel method), [1], [2] compute_canonical_loss() (AbstractGaussianNoiseModel class method), [1], [2] (AbstractOrdinalNoiseModel method), [1], [2] (BaseNoiseModel method), [1], [2] (BernoulliNoiseModel method), [1], [2] (GaussianDiagonalNoiseModel class method), [1], [2] (GaussianScalarNoiseModel class method), [1], [2] (OrdinalNoiseModel method), [1], [2] (OrdinalRankingNoiseModel method), [1], [2] compute_canonical_loss_tensorized() (AbstractModel method), [1], [2] (AbstractMultivariateModel method), [1], [2] (MultivariateModel method), [1], [2] (MultivariateParallelModel method), [1], [2] (UnivariateModel method), [1], [2] compute_individual_ages_from_biomarker_values() (AbstractModel method), [1], [2] (AbstractMultivariateModel method), [1], [2] (MultivariateModel method), [1], [2] (MultivariateParallelModel method), [1], [2] (UnivariateModel method), [1], [2] compute_individual_ages_from_biomarker_values_tensorized() (AbstractModel method), [1], [2] (AbstractMultivariateModel method), [1], [2] (MultivariateModel method), [1], [2] (MultivariateParallelModel method), [1], [2] (UnivariateModel method), [1], [2] compute_individual_ages_from_biomarker_values_tensorized_logistic() (MultivariateModel method), [1], [2] (UnivariateModel method), [1], [2] compute_individual_attachment_tensorized() (AbstractModel method), [1], [2] (AbstractMultivariateModel method), [1], [2] (MultivariateModel method), [1], [2] (MultivariateParallelModel method), [1], [2] (UnivariateModel method), [1], [2] compute_individual_tensorized() (AbstractModel method), [1], [2] (AbstractMultivariateModel method), [1], [2] (MultivariateModel method), [1], [2] (MultivariateParallelModel method), [1], [2] (UnivariateModel method), [1], [2] compute_individual_tensorized_linear() (MultivariateModel method), [1], [2] (UnivariateModel method), [1], [2] compute_individual_tensorized_logistic() (MultivariateModel method), [1], [2] (UnivariateModel method), [1], [2] compute_individual_trajectory() (AbstractModel method), [1], [2] (AbstractMultivariateModel method), [1], [2] (ConstantModel method), [1], [2] (GenericModel method), [1], [2] (LMEModel method), [1], [2] (MultivariateModel method), [1], [2] (MultivariateParallelModel method), [1], [2] (UnivariateModel method), [1], [2] compute_jacobian_tensorized() (AbstractModel method), [1], [2] (AbstractMultivariateModel method), [1], [2] (MultivariateModel method), [1], [2] (MultivariateParallelModel method), [1], [2] (UnivariateModel method), [1], [2] compute_jacobian_tensorized_linear() (MultivariateModel method), [1], [2] (UnivariateModel method), [1], [2] compute_jacobian_tensorized_logistic() (MultivariateModel method), [1], [2] (UnivariateModel method), [1], [2] compute_l2_residuals() (AbstractGaussianNoiseModel class method), [1], [2] (GaussianDiagonalNoiseModel class method), [1], [2] (GaussianScalarNoiseModel class method), [1], [2]

compute_linregress_subjects() (in module leaspy.models.utils.initialization.model_initialization) compute_mean_traj() (AbstractMultivariateModel method), [1], [2] (MultivariateModel method), [1], [2] (MultivariateParallelModel method), [1], [2] (UnivariateModel method), [1], [2] compute_model_sufficient_statistics() (AbstractModel method), [1], [2] (AbstractMultivariateModel method), [1], [2] (MultivariateModel method), [1], [2] (MultivariateParallelModel method), [1], [2] (UnivariateModel method), [1], [2] compute_nll() (AbstractGaussianNoiseModel method), [1], [2] (AbstractOrdinalNoiseModel method), [1], [2] (BaseNoiseModel method), [1], [2] (BernoulliNoiseModel method), [1], [2] (GaussianDiagonalNoiseModel method), [1], [2] (GaussianScalarNoiseModel method), [1], [2] (OrdinalNoiseModel method), [1], [2] (OrdinalRankingNoiseModel method), [1], [2] compute_ordinal_model_sufficient_statistics() (AbstractMultivariateModel method), [1], [2] (MultivariateModel method), [1], [2] (MultivariateParallelModel method), [1], [2] (OrdinalModelMixin method) (UnivariateModel method), [1], [2] compute_ordinal_pdf_from_ordinal_sf() (AbstractMultivariateModel static method), [1], [2] (MultivariateModel static method), [1], [2] (MultivariateParallelModel static method), [1], [2] (OrdinalModelMixin static method) (UnivariateModel static method), [1], [2] compute_patient_slopes_distribution() (in module leaspy.models.utils.initialization.model_initialization) compute_patient_time_distribution() (in module leaspy.models.utils.initialization.model_initialization) compute_patient_values_distribution() (in module leaspy.models.utils.initialization.model_initialization) compute_regularity_individual_parameters() (AbstractModel method), [1], [2] (AbstractMultivariateModel method), [1], [2] (MultivariateModel method), [1], [2] (MultivariateParallelModel method), [1], [2] (UnivariateModel method), [1], [2] compute_regularity_individual_realization() (AbstractModel method), [1], [2] (AbstractMultivariateModel method), [1], [2] (MultivariateModel method), [1], [2] (MultivariateParallelModel method), [1], [2] (UnivariateModel method), [1], [2] compute_regularity_population_realization() (AbstractModel method), [1], [2] (AbstractMultivariateModel method), [1], [2] (MultivariateModel method), [1], [2] (MultivariateParallelModel method), [1], [2] (UnivariateModel method), [1], [2] compute_regularity_realization() (AbstractModel method), [1], [2] (AbstractMultivariateModel method), [1], [2] (MultivariateModel method), [1], [2] (MultivariateParallelModel method), [1], [2] (UnivariateModel method), [1], [2] compute_regularity_variable() (AbstractModel method), [1], [2] (AbstractMultivariateModel method), [1], [2] (MultivariateModel method), [1], [2] (MultivariateParallelModel method), [1], [2] (UnivariateModel method), [1], [2] compute_residuals() (AbstractGaussianNoiseModel static method), [1], [2] (GaussianDiagonalNoiseModel static method), [1], [2] (GaussianScalarNoiseModel static method), [1], [2] compute_rmse() (AbstractGaussianNoiseModel class method), [1], [2] (GaussianDiagonalNoiseModel class method), [1], [2] (GaussianScalarNoiseModel class method), [1], [2] compute_std_from_variance() (in module leaspy.models.utilities) compute_sufficient_statistics() (AbstractGaussianNoiseModel method), [1], [2] (AbstractModel method), [1], [2] (AbstractMultivariateModel method), [1], [2] (AbstractOrdinalNoiseModel method), [1], [2] (BaseNoiseModel method), [1], [2] (BernoulliNoiseModel method), [1], [2] (GaussianDiagonalNoiseModel method), [1], [2] (GaussianScalarNoiseModel method), [1], [2] (MultivariateModel method), [1], [2] (MultivariateParallelModel method), [1], [2] (OrdinalNoiseModel method), [1], [2] (OrdinalRankingNoiseModel method), [1], [2] (UnivariateModel method), [1], [2] constant_return_factory() (in module leaspy.models.noise_models.base) ConstantModel (class in leaspy.models), [1] (class in leaspy.models.constant) ConstantPredictionAlgorithm (class in leaspy.algo.others.constant_prediction_algo), [1] CSVDataReader (class in leaspy.io.data.csv_data_reader) current_iteration (AbstractFitMCMC attribute) (MeanReal attribute) (ModeReal attribute) (TensorMCMCSAEM attribute)

D

Data (class in leaspy.io.data.data), [1] DataframeDataReader (class in leaspy.io.data.dataframe_data_reader) Dataset (class in leaspy.io.data.dataset), [1] DEFAULT_FORMAT_CONVERGENCE_ISSUES (ScipyMinimize attribute) DEFAULT_LOGS_DIR (OutputsSettings attribute) DEFAULT_SCIPY_MINIMIZE_PARAMS_WITH_JACOBIAN (ScipyMinimize attribute) DEFAULT_SCIPY_MINIMIZE_PARAMS_WITHOUT_JACOBIAN (ScipyMinimize attribute) deterministic (AbstractAlgo attribute) (AbstractFitAlgo attribute) (AbstractFitMCMC attribute) (AbstractMCMCPersonalizeAlgo attribute) (AbstractPersonalizeAlgo attribute) (ConstantPredictionAlgorithm attribute) (LMEFitAlgorithm attribute) (LMEPersonalizeAlgorithm attribute) (MeanReal attribute) (ModeReal attribute) (ScipyMinimize attribute) (SimulationAlgorithm attribute) (TensorMCMCSAEM attribute)

DictRealizations (class in leaspy.io.realizations), [1] (class in leaspy.io.realizations.dict_realizations) dimension (AbstractModel property), [1], [2] (AbstractMultivariateModel property), [1], [2] (BaseModel property), [1], [2] (ConstantModel property), [1], [2] (CSVDataReader property) (Data property), [1] (DataframeDataReader property) (GenericModel property), [1], [2] (LMEModel property), [1], [2] (MultivariateModel property), [1], [2] (MultivariateParallelModel property), [1], [2] (UnivariateModel property), [1], [2] discrete_sf_from_pdf() (in module leaspy.utils.distributions) DistributionFamily (class in leaspy.models.noise_models), [1] (class in leaspy.models.noise_models.base) doc_with() (in module leaspy.utils.docs) doc_with_() (in module leaspy.utils.docs) doc_with_super() (in module leaspy.utils.docs)

E

entropy() (MultinomialDistribution method) enumerate_support() (MultinomialDistribution method) estimate() (Leaspy method), [1] estimate_ages_from_biomarker_values() (Leaspy method), [1]

estimation event_shape (MultinomialDistribution property) expand() (MultinomialDistribution method) export_noise_model() (in module leaspy.models.noise_models), [1] (in module leaspy.models.noise_models.factory)

F

factory (AbstractGaussianNoiseModel attribute), [1], [2] (AbstractOrdinalNoiseModel attribute), [1] (BaseNoiseModel attribute), [1] (BernoulliFamily attribute) (BernoulliNoiseModel attribute), [1], [2] (DistributionFamily attribute), [1] (GaussianDiagonalNoiseModel attribute), [1], [2] (GaussianFamily attribute) (GaussianScalarNoiseModel attribute), [1], [2] (NoNoise attribute) (OrdinalRankingFamily attribute) (OrdinalRankingNoiseModel attribute), [1], [2] factory() (OrdinalFamily class method) (OrdinalNoiseModel class method), [1], [2] family (AbstractAlgo attribute) (AbstractFitAlgo attribute) (AbstractFitMCMC attribute) (AbstractMCMCPersonalizeAlgo attribute) (AbstractPersonalizeAlgo attribute) (ConstantPredictionAlgorithm attribute) (LMEFitAlgorithm attribute) (LMEPersonalizeAlgorithm attribute) (MeanReal attribute) (ModeReal attribute) (ScipyMinimize attribute) (SimulationAlgorithm attribute) (TensorMCMCSAEM attribute) features (AbstractModel property), [1] (AbstractMultivariateModel property), [1] (BaseModel property), [1] (ConstantModel property), [1] (GenericModel property), [1] (LMEModel property), [1] (MultivariateModel property), [1] (MultivariateParallelModel property), [1] (UnivariateModel property), [1]

fit() (Leaspy method), [1] FitOutputManager (class in leaspy.io.logs.fit_output_manager) fixed effects model free_parameters (AbstractGaussianNoiseModel attribute), [1] (AbstractOrdinalNoiseModel attribute), [1] (BaseNoiseModel attribute), [1] (BernoulliFamily attribute) (BernoulliNoiseModel attribute), [1] (DistributionFamily attribute), [1] (GaussianDiagonalNoiseModel attribute), [1] (GaussianFamily attribute) (GaussianScalarNoiseModel attribute), [1] (NoNoise attribute) (OrdinalFamily attribute) (OrdinalNoiseModel attribute), [1] (OrdinalRankingFamily attribute) (OrdinalRankingNoiseModel attribute), [1] from_csv_file() (Data static method), [1] from_dataframe() (Data static method), [1] (IndividualParameters static method), [1] from_individual_values() (Data static method), [1] from_individuals() (Data static method), [1] from_pdf() (MultinomialDistribution class method) from_pytorch() (IndividualParameters static method), [1] from_string() (VariableType class method), [1]

G

GaussianDiagonalNoiseModel (class in leaspy.models.noise_models), [1] (class in leaspy.models.noise_models.gaussian) GaussianFamily (class in leaspy.models.noise_models.gaussian) GaussianScalarNoiseModel (class in leaspy.models.noise_models), [1] (class in leaspy.models.noise_models.gaussian) GenericModel (class in leaspy.models), [1] (class in leaspy.models.generic) get_additional_ordinal_population_random_variable_information() (AbstractMultivariateModel method), [1], [2] (MultivariateModel method), [1], [2] (MultivariateParallelModel method), [1], [2] (OrdinalModelMixin method) (UnivariateModel method), [1], [2] get_aggregate() (IndividualParameters method), [1] get_attributes() (AbstractAttributes method), [1] (AbstractManifoldModelAttributes method), [1] (LinearAttributes method), [1] (LogisticAttributes method), [1] (LogisticOrdinalAttributes method) (LogisticParallelAttributes method), [1] get_class() (AlgoFactory class method), [1] get_cofactor_distribution() (Result method) get_cofactor_states() (Result static method) get_dataframe_individual_parameters() (Result method) get_deltas() (LogisticOrdinalAttributes method) get_error_distribution_dataframe() (Result method) get_hyperparameters() (ConstantModel method), [1], [2] (GenericModel method), [1], [2] (LMEModel method), [1], [2] get_individual_random_variable_information() (AbstractModel method), [1], [2] (AbstractMultivariateModel method), [1], [2] (MultivariateModel method), [1], [2] (MultivariateParallelModel method), [1], [2] (UnivariateModel method), [1], [2]

get_individual_variable_names() (AbstractModel method), [1], [2] (AbstractMultivariateModel method), [1], [2] (MultivariateModel method), [1], [2] (MultivariateParallelModel method), [1], [2] (UnivariateModel method), [1], [2] get_lme_results() (in module leaspy.models.utils.initialization.model_initialization) get_log_velocities() (in module leaspy.models.utils.initialization.model_initialization) get_mean() (IndividualParameters method), [1] get_one_hot_encoding() (Dataset method), [1] get_ordinal_parameters_updates_from_sufficient_statistics() (AbstractMultivariateModel method), [1], [2] (MultivariateModel method), [1], [2] (MultivariateParallelModel method), [1], [2] (OrdinalModelMixin method) (UnivariateModel method), [1], [2] get_parameter_distribution() (Result method) get_patient_individual_parameters() (Result method) get_population_random_variable_information() (AbstractModel method), [1], [2] (AbstractMultivariateModel method), [1], [2] (MultivariateModel method), [1], [2] (MultivariateParallelModel method), [1], [2] (UnivariateModel method), [1], [2] get_population_variable_names() (AbstractModel method), [1], [2] (AbstractMultivariateModel method), [1], [2] (MultivariateModel method), [1], [2] (MultivariateParallelModel method), [1], [2] (UnivariateModel method), [1], [2] get_std() (IndividualParameters method), [1] get_times_patient() (Dataset method), [1] get_torch_individual_parameters() (Result method) get_values_patient() (Dataset method), [1] GibbsSamplerMixin (class in leaspy.samplers.gibbs)

H

has_enumerate_support (MultinomialDistribution attribute) has_rsample (MultinomialDistribution attribute)

hyperparameters_ok() (ConstantModel method), [1], [2] (GenericModel method), [1], [2] (LMEModel method), [1], [2]

I

icdf() (MultinomialDistribution method) individual (CollectionRealization property), [1] INDIVIDUAL (VariableType attribute), [1] IndividualData (class in leaspy.io.data.individual_data) IndividualGibbsSampler (class in leaspy.samplers), [1] (class in leaspy.samplers.gibbs) IndividualParameters (class in leaspy.io.outputs.individual_parameters), [1] IndividualRealization (class in leaspy.io.realizations), [1] (class in leaspy.io.realizations.realization) initialize() (AbstractModel method), [1], [2] (AbstractMultivariateModel method), [1], [2] (AbstractRealization method), [1], [2] (BaseModel method), [1], [2] (CollectionRealization method), [1], [2] (ConstantModel method), [1], [2] (GenericModel method), [1], [2] (IndividualRealization method), [1], [2] (LMEModel method), [1], [2] (MultivariateModel method), [1], [2] (MultivariateParallelModel method), [1], [2] (PopulationRealization method), [1], [2] (UnivariateModel method), [1], [2] initialize_around_mean() (IndividualRealization method), [1], [2] initialize_at_mean() (IndividualRealization method), [1], [2] initialize_deltas_ordinal() (in module leaspy.models.utils.initialization.model_initialization) initialize_individuals() (CollectionRealization method), [1], [2]

initialize_linear() (in module leaspy.models.utils.initialization.model_initialization) initialize_logistic() (in module leaspy.models.utils.initialization.model_initialization) initialize_logistic_parallel() (in module leaspy.models.utils.initialization.model_initialization) initialize_MCMC_toolbox() (AbstractMultivariateModel method), [1], [2] (MultivariateModel method), [1], [2] (MultivariateParallelModel method), [1], [2] (UnivariateModel method), [1], [2] initialize_parameters() (in module leaspy.models.utils.initialization.model_initialization), [1] initialize_population() (CollectionRealization method), [1], [2] is_initialized (MultivariateModel attribute) (UnivariateModel attribute), [1] is_jacobian_implemented() (ScipyMinimize method), [1] is_ordinal (AbstractMultivariateModel property), [1], [2] (MultivariateModel property), [1], [2] (MultivariateParallelModel property), [1], [2] (OrdinalModelMixin property) (UnivariateModel property), [1], [2] is_ordinal_ranking (AbstractMultivariateModel property), [1], [2] (MultivariateModel property), [1], [2] (MultivariateParallelModel property), [1], [2] (OrdinalModelMixin property) (UnivariateModel property), [1], [2] items() (IndividualParameters method), [1] iteration() (AbstractFitAlgo method), [1] (AbstractFitMCMC method), [1] (FitOutputManager method) (TensorMCMCSAEM method), [1]

J

JSON

L

leaspy module Leaspy (class in leaspy.api), [1] leaspy.algo module leaspy.algo.abstract_algo module leaspy.algo.algo_factory module leaspy.algo.fit module leaspy.algo.fit.abstract_fit_algo module leaspy.algo.fit.abstract_mcmc module leaspy.algo.fit.tensor_mcmcsaem module leaspy.algo.others module leaspy.algo.others.constant_prediction_algo module leaspy.algo.others.lme_fit module leaspy.algo.others.lme_personalize module leaspy.algo.personalize module leaspy.algo.personalize.abstract_mcmc_personalize module leaspy.algo.personalize.abstract_personalize_algo module leaspy.algo.personalize.mean_realisations module leaspy.algo.personalize.mode_realisations module leaspy.algo.personalize.scipy_minimize module leaspy.algo.simulate module leaspy.algo.simulate.simulate module leaspy.algo.utils module leaspy.algo.utils.algo_with_annealing module leaspy.algo.utils.algo_with_device module leaspy.algo.utils.algo_with_samplers module leaspy.api module leaspy.datasets module leaspy.datasets.loader module leaspy.exceptions module leaspy.io module leaspy.io.data module leaspy.io.data.csv_data_reader module leaspy.io.data.data module leaspy.io.data.dataframe_data_reader module leaspy.io.data.dataset module leaspy.io.data.individual_data module leaspy.io.logs module leaspy.io.logs.fit_output_manager module leaspy.io.logs.visualization module leaspy.io.logs.visualization.plotter module leaspy.io.logs.visualization.plotting module leaspy.io.outputs module leaspy.io.outputs.individual_parameters module leaspy.io.outputs.result module leaspy.io.realizations module leaspy.io.realizations.collection_realization module leaspy.io.realizations.dict_realizations module leaspy.io.realizations.factory module leaspy.io.realizations.realization module leaspy.io.settings module leaspy.io.settings.algorithm_settings module leaspy.io.settings.model_settings module leaspy.io.settings.outputs_settings module leaspy.models module leaspy.models.abstract_model module leaspy.models.abstract_multivariate_model module leaspy.models.base module leaspy.models.constant module leaspy.models.factory module leaspy.models.generic module leaspy.models.lme module leaspy.models.multivariate module

leaspy.models.multivariate_parallel module leaspy.models.noise_models module leaspy.models.noise_models.base module leaspy.models.noise_models.bernoulli module leaspy.models.noise_models.factory module leaspy.models.noise_models.gaussian module leaspy.models.noise_models.ordinal module leaspy.models.univariate module leaspy.models.utilities module leaspy.models.utils module leaspy.models.utils.attributes module leaspy.models.utils.attributes.abstract_attributes module leaspy.models.utils.attributes.abstract_manifold_model_attributes module leaspy.models.utils.attributes.attributes_factory module leaspy.models.utils.attributes.linear_attributes module leaspy.models.utils.attributes.logistic_attributes module leaspy.models.utils.attributes.logistic_ordinal_attributes module leaspy.models.utils.attributes.logistic_parallel_attributes module leaspy.models.utils.initialization module leaspy.models.utils.initialization.model_initialization module leaspy.models.utils.ordinal module leaspy.samplers module leaspy.samplers.base module leaspy.samplers.factory module leaspy.samplers.gibbs module leaspy.utils module leaspy.utils.distributions module leaspy.utils.docs module leaspy.utils.subtypes module leaspy.utils.typing module LeaspyAlgoInputError, [1] LeaspyConvergenceError, [1] LeaspyDataInputError, [1] LeaspyException, [1] LeaspyIndividualParamsInputError, [1] LeaspyInputError, [1] LeaspyModelInputError, [1] LeaspyTypeError, [1] likelihood LinearAttributes (class in leaspy.models.utils.attributes.linear_attributes), [1] linregress_against_time() (in module leaspy.models.utils.initialization.model_initialization) lme_init() (in module leaspy.models.utils.initialization.model_initialization) LMEFitAlgorithm (class in leaspy.algo.others.lme_fit), [1] LMEModel (class in leaspy.models), [1] (class in leaspy.models.lme) LMEPersonalizeAlgorithm (class in leaspy.algo.others.lme_personalize), [1] load() (AlgorithmSettings class method), [1] (IndividualParameters class method), [1] (Leaspy class method), [1] load_cofactors() (Data method), [1] load_dataset() (Loader static method), [1] load_hyperparameters() (AbstractModel method), [1], [2] (AbstractMultivariateModel method), [1], [2] (ConstantModel method), [1], [2] (GenericModel method), [1], [2] (LMEModel method), [1], [2] (MultivariateModel method), [1], [2] (MultivariateParallelModel method), [1], [2] (UnivariateModel method), [1], [2] load_individual_parameters() (Loader static method), [1] (Result class method) load_individual_parameters_from_csv() (Result class method) load_individual_parameters_from_dataframe() (Result static method) load_individual_parameters_from_json() (Result static method) load_individual_parameters_from_torch() (Result static method) load_leaspy_instance() (Loader static method), [1] load_parameters() (AbstractAlgo method), [1] (AbstractFitAlgo method), [1] (AbstractFitMCMC method), [1] (AbstractMCMCPersonalizeAlgo method) (AbstractModel method), [1], [2] (AbstractMultivariateModel method), [1], [2] (AbstractPersonalizeAlgo method), [1] (ConstantModel method), [1], [2] (ConstantPredictionAlgorithm method), [1] (GenericModel method), [1], [2] (LMEFitAlgorithm method), [1] (LMEModel method), [1], [2] (LMEPersonalizeAlgorithm method), [1] (MeanReal method) (ModeReal method) (MultivariateModel method), [1], [2] (MultivariateParallelModel method), [1], [2] (ScipyMinimize method), [1] (SimulationAlgorithm method), [1] (TensorMCMCSAEM method), [1] (UnivariateModel method), [1], [2] load_result() (Result class method) Loader (class in leaspy.datasets.loader), [1] log_prob() (MultinomialDistribution method) LogisticAttributes (class in leaspy.models.utils.attributes.logistic_attributes), [1] LogisticOrdinalAttributes (class in leaspy.models.utils.attributes.logistic_ordinal_attributes) LogisticParallelAttributes (class in leaspy.models.utils.attributes.logistic_parallel_attributes), [1]

M

mask (AbstractOrdinalNoiseModel property), [1] (OrdinalNoiseModel property), [1] (OrdinalRankingNoiseModel property), [1] max_level (AbstractOrdinalNoiseModel property), [1] (OrdinalNoiseModel property), [1] (OrdinalRankingNoiseModel property), [1] max_levels (AbstractOrdinalNoiseModel attribute), [1] (OrdinalNoiseModel attribute), [1] (OrdinalRankingNoiseModel attribute), [1] MCMC MCMC-SAEM mean (MultinomialDistribution property) MeanReal (class in leaspy.algo.personalize.mean_realisations) mixed model mixing matrix MMSE model() (ModelFactory static method), [1], [2] ModelFactory (class in leaspy.models), [1] (class in leaspy.models.factory) ModelSettings (class in leaspy.io.settings.model_settings), [1] ModeReal (class in leaspy.algo.personalize.mode_realisations) module leaspy leaspy.algo leaspy.algo.abstract_algo leaspy.algo.algo_factory leaspy.algo.fit leaspy.algo.fit.abstract_fit_algo leaspy.algo.fit.abstract_mcmc leaspy.algo.fit.tensor_mcmcsaem leaspy.algo.others leaspy.algo.others.constant_prediction_algo leaspy.algo.others.lme_fit leaspy.algo.others.lme_personalize leaspy.algo.personalize leaspy.algo.personalize.abstract_mcmc_personalize leaspy.algo.personalize.abstract_personalize_algo leaspy.algo.personalize.mean_realisations leaspy.algo.personalize.mode_realisations leaspy.algo.personalize.scipy_minimize leaspy.algo.simulate leaspy.algo.simulate.simulate leaspy.algo.utils leaspy.algo.utils.algo_with_annealing leaspy.algo.utils.algo_with_device leaspy.algo.utils.algo_with_samplers leaspy.api leaspy.datasets leaspy.datasets.loader leaspy.exceptions leaspy.io leaspy.io.data leaspy.io.data.csv_data_reader leaspy.io.data.data leaspy.io.data.dataframe_data_reader leaspy.io.data.dataset leaspy.io.data.individual_data leaspy.io.logs leaspy.io.logs.fit_output_manager leaspy.io.logs.visualization leaspy.io.logs.visualization.plotter leaspy.io.logs.visualization.plotting leaspy.io.outputs leaspy.io.outputs.individual_parameters leaspy.io.outputs.result leaspy.io.realizations leaspy.io.realizations.collection_realization leaspy.io.realizations.dict_realizations leaspy.io.realizations.factory leaspy.io.realizations.realization leaspy.io.settings leaspy.io.settings.algorithm_settings leaspy.io.settings.model_settings leaspy.io.settings.outputs_settings leaspy.models leaspy.models.abstract_model leaspy.models.abstract_multivariate_model leaspy.models.base leaspy.models.constant leaspy.models.factory leaspy.models.generic leaspy.models.lme leaspy.models.multivariate leaspy.models.multivariate_parallel leaspy.models.noise_models leaspy.models.noise_models.base leaspy.models.noise_models.bernoulli leaspy.models.noise_models.factory leaspy.models.noise_models.gaussian leaspy.models.noise_models.ordinal leaspy.models.univariate leaspy.models.utilities leaspy.models.utils leaspy.models.utils.attributes leaspy.models.utils.attributes.abstract_attributes leaspy.models.utils.attributes.abstract_manifold_model_attributes leaspy.models.utils.attributes.attributes_factory leaspy.models.utils.attributes.linear_attributes leaspy.models.utils.attributes.logistic_attributes leaspy.models.utils.attributes.logistic_ordinal_attributes leaspy.models.utils.attributes.logistic_parallel_attributes leaspy.models.utils.initialization leaspy.models.utils.initialization.model_initialization leaspy.models.utils.ordinal leaspy.samplers leaspy.samplers.base leaspy.samplers.factory leaspy.samplers.gibbs leaspy.utils leaspy.utils.distributions leaspy.utils.docs leaspy.utils.subtypes leaspy.utils.typing

move_to_device() (AbstractAttributes method), [1] (AbstractGaussianNoiseModel method), [1], [2] (AbstractManifoldModelAttributes method), [1] (AbstractModel method), [1], [2] (AbstractMultivariateModel method), [1], [2] (AbstractOrdinalNoiseModel method), [1], [2] (BaseNoiseModel method), [1], [2] (BernoulliFamily method) (BernoulliNoiseModel method), [1], [2] (Dataset method), [1] (DistributionFamily method), [1], [2] (GaussianDiagonalNoiseModel method), [1], [2] (GaussianFamily method) (GaussianScalarNoiseModel method), [1], [2] (LinearAttributes method), [1] (LogisticAttributes method), [1] (LogisticOrdinalAttributes method) (LogisticParallelAttributes method), [1] (MultivariateModel method), [1], [2] (MultivariateParallelModel method), [1], [2] (NoNoise method) (OrdinalFamily method) (OrdinalNoiseModel method), [1], [2] (OrdinalRankingFamily method) (OrdinalRankingNoiseModel method), [1], [2] (UnivariateModel method), [1], [2] MultinomialDistribution (class in leaspy.utils.distributions) MultivariateModel (class in leaspy.models), [1] (class in leaspy.models.multivariate) MultivariateParallelModel (class in leaspy.models), [1] (class in leaspy.models.multivariate_parallel)

N

n_individuals (Data property), [1] n_visits (Data property), [1] name (AbstractAlgo attribute) (AbstractFitAlgo attribute) (AbstractFitMCMC attribute) (AbstractMCMCPersonalizeAlgo attribute) (AbstractPersonalizeAlgo attribute) (ConstantPredictionAlgorithm attribute) (LMEFitAlgorithm attribute) (LMEPersonalizeAlgorithm attribute) (MeanReal attribute) (ModeReal attribute) (ScipyMinimize attribute) (SimulationAlgorithm attribute) (TensorMCMCSAEM attribute)

names (CollectionRealization property), [1], [2] (DictRealizations property), [1], [2] noise_model (AbstractModel property), [1] (AbstractMultivariateModel property), [1] (MultivariateModel property), [1] (MultivariateParallelModel property), [1] (UnivariateModel property), [1] noise_model_factory() (in module leaspy.models.noise_models), [1] (in module leaspy.models.noise_models.factory) NoNoise (class in leaspy.models.noise_models.base)

O

obj() (ScipyMinimize method), [1] ordinal_infos (AbstractMultivariateModel property), [1], [2] (AbstractOrdinalNoiseModel property), [1] (MultivariateModel property), [1], [2] (MultivariateParallelModel property), [1], [2] (OrdinalModelMixin property) (OrdinalNoiseModel property), [1] (OrdinalRankingNoiseModel property), [1] (UnivariateModel property), [1], [2] OrdinalFamily (class in leaspy.models.noise_models.ordinal) OrdinalModelMixin (class in leaspy.models.utils.ordinal) OrdinalNoiseModel (class in leaspy.models.noise_models), [1] (class in leaspy.models.noise_models.ordinal) OrdinalRankingFamily (class in leaspy.models.noise_models.ordinal) OrdinalRankingNoiseModel (class in leaspy.models.noise_models), [1] (class in leaspy.models.noise_models.ordinal)

output_manager (AbstractFitAlgo attribute) (AbstractFitMCMC attribute) (AbstractMCMCPersonalizeAlgo attribute) (AbstractPersonalizeAlgo attribute) (ConstantPredictionAlgorithm attribute) (LMEFitAlgorithm attribute) (LMEPersonalizeAlgorithm attribute) (MeanReal attribute) (ModeReal attribute) (ScipyMinimize attribute) (SimulationAlgorithm attribute) (TensorMCMCSAEM attribute) OutputsSettings (class in leaspy.io.settings.outputs_settings), [1] overfitting

P

parameters (AbstractGaussianNoiseModel attribute), [1] (AbstractOrdinalNoiseModel attribute), [1] (BaseNoiseModel attribute), [1] (BernoulliFamily attribute) (BernoulliNoiseModel attribute), [1] (DistributionFamily attribute), [1] (GaussianDiagonalNoiseModel attribute), [1] (GaussianFamily attribute) (GaussianScalarNoiseModel attribute), [1] (MultivariateModel attribute) (NoNoise attribute) (OrdinalFamily attribute) (OrdinalNoiseModel attribute), [1] (OrdinalRankingFamily attribute) (OrdinalRankingNoiseModel attribute), [1] (UnivariateModel attribute), [1] patient_observations() (Plotting method) patient_observations_reparametrized() (Plotting method) patient_trajectories() (Plotting method) perplexity() (MultinomialDistribution method) personalization personalize() (Leaspy method), [1] plot_convergence_model_parameters() (FitOutputManager method) (Plotter static method) plot_correlation() (Plotter method) plot_distribution() (Plotter method) plot_error() (Plotter class method) plot_from_individual_parameters() (Plotter method)

plot_mean_trajectory() (Plotter method) plot_mean_validity() (Plotter method) plot_param_ind() (Plotter static method) plot_patient_reconstructions() (FitOutputManager method) (Plotter class method) plot_patient_trajectory() (Plotter method) plot_patients_mapped_on_mean_trajectory() (Plotter method) Plotter (class in leaspy.io.logs.visualization.plotter) Plotting (class in leaspy.io.logs.visualization.plotting) plt_show() (Plotter method) population (CollectionRealization property), [1] POPULATION (VariableType attribute), [1] PopulationFastGibbsSampler (class in leaspy.samplers), [1] (class in leaspy.samplers.gibbs) PopulationGibbsSampler (class in leaspy.samplers), [1] (class in leaspy.samplers.gibbs) PopulationMetropolisHastingsSampler (class in leaspy.samplers), [1] (class in leaspy.samplers.gibbs) PopulationRealization (class in leaspy.io.realizations), [1] (class in leaspy.io.realizations.realization) postprocess_model_estimation() (AbstractMultivariateModel method), [1], [2] (MultivariateModel method), [1], [2] (MultivariateParallelModel method), [1], [2] (OrdinalModelMixin method) (UnivariateModel method), [1], [2] print_algo_statistics() (FitOutputManager method) print_model_statistics() (FitOutputManager method) print_time() (FitOutputManager method)

R

raise_if_partially_defined() (AbstractGaussianNoiseModel method), [1], [2] (AbstractOrdinalNoiseModel method), [1], [2] (BaseNoiseModel method), [1], [2] (BernoulliFamily method) (BernoulliNoiseModel method), [1], [2] (DistributionFamily method), [1], [2] (GaussianDiagonalNoiseModel method), [1], [2] (GaussianFamily method) (GaussianScalarNoiseModel method), [1], [2] (NoNoise method) (OrdinalFamily method) (OrdinalNoiseModel method), [1], [2] (OrdinalRankingFamily method) (OrdinalRankingNoiseModel method), [1], [2] raise_if_unknown_parameters() (AbstractGaussianNoiseModel class method), [1], [2] (AbstractOrdinalNoiseModel class method), [1], [2] (BaseNoiseModel class method), [1], [2] (BernoulliFamily class method) (BernoulliNoiseModel class method), [1], [2] (DistributionFamily class method), [1], [2] (GaussianDiagonalNoiseModel class method), [1], [2] (GaussianFamily class method) (GaussianScalarNoiseModel class method), [1], [2] (NoNoise class method) (OrdinalFamily class method) (OrdinalNoiseModel class method), [1], [2] (OrdinalRankingFamily class method) (OrdinalRankingNoiseModel class method), [1], [2] random effects model realization_factory() (in module leaspy.io.realizations), [1] (in module leaspy.io.realizations.factory) realizations (CollectionRealization property), [1] (DictRealizations property), [1] realizations_dict (CollectionRealization property), [1], [2] regularity regularization Result (class in leaspy.io.outputs.result) rsample() (MultinomialDistribution method) run() (AbstractAlgo method), [1] (AbstractFitAlgo method), [1] (AbstractFitMCMC method), [1] (AbstractMCMCPersonalizeAlgo method) (AbstractPersonalizeAlgo method), [1] (ConstantPredictionAlgorithm method), [1] (LMEFitAlgorithm method), [1] (LMEPersonalizeAlgorithm method), [1] (MeanReal method) (ModeReal method) (ScipyMinimize method), [1] (SimulationAlgorithm method), [1] (TensorMCMCSAEM method), [1]

run_impl() (AbstractAlgo method), [1] (AbstractFitAlgo method), [1] (AbstractFitMCMC method), [1] (AbstractMCMCPersonalizeAlgo method) (AbstractPersonalizeAlgo method), [1] (ConstantPredictionAlgorithm method), [1] (LMEFitAlgorithm method), [1] (LMEPersonalizeAlgorithm method), [1] (MeanReal method) (ModeReal method) (ScipyMinimize method), [1] (SimulationAlgorithm method), [1] (TensorMCMCSAEM method), [1] rv_around() (AbstractGaussianNoiseModel method), [1], [2] (AbstractOrdinalNoiseModel method), [1], [2] (BaseNoiseModel method), [1], [2] (BernoulliFamily method) (BernoulliNoiseModel method), [1], [2] (DistributionFamily method), [1], [2] (GaussianDiagonalNoiseModel method), [1], [2] (GaussianFamily method) (GaussianScalarNoiseModel method), [1], [2] (NoNoise method) (OrdinalFamily method) (OrdinalNoiseModel method), [1], [2] (OrdinalRankingFamily method) (OrdinalRankingNoiseModel method), [1], [2]

S

sample() (AbstractIndividualSampler method), [1], [2] (AbstractPopulationGibbsSampler method) (AbstractPopulationSampler method), [1], [2] (AbstractSampler method), [1], [2] (IndividualGibbsSampler method), [1], [2] (MultinomialDistribution method) (PopulationFastGibbsSampler method), [1], [2] (PopulationGibbsSampler method), [1], [2] (PopulationMetropolisHastingsSampler method), [1], [2] sample_around() (AbstractGaussianNoiseModel method), [1], [2] (AbstractOrdinalNoiseModel method), [1], [2] (BaseNoiseModel method), [1], [2] (BernoulliFamily method) (BernoulliNoiseModel method), [1], [2] (DistributionFamily method), [1], [2] (GaussianDiagonalNoiseModel method), [1], [2] (GaussianFamily method) (GaussianScalarNoiseModel method), [1], [2] (NoNoise method) (OrdinalFamily method) (OrdinalNoiseModel method), [1], [2] (OrdinalRankingFamily method) (OrdinalRankingNoiseModel method), [1], [2] sample_n() (MultinomialDistribution method) sampler_around() (AbstractGaussianNoiseModel method), [1], [2] (AbstractOrdinalNoiseModel method), [1], [2] (BaseNoiseModel method), [1], [2] (BernoulliFamily method) (BernoulliNoiseModel method), [1], [2] (DistributionFamily method), [1], [2] (GaussianDiagonalNoiseModel method), [1], [2] (GaussianFamily method) (GaussianScalarNoiseModel method), [1], [2] (NoNoise method) (OrdinalFamily method) (OrdinalNoiseModel method), [1], [2] (OrdinalRankingFamily method) (OrdinalRankingNoiseModel method), [1], [2] sampler_factory() (in module leaspy.samplers), [1] (in module leaspy.samplers.factory) samplers (MeanReal attribute) (ModeReal attribute) (TensorMCMCSAEM attribute) save() (AbstractModel method), [1], [2] (AbstractMultivariateModel method), [1], [2] (AlgorithmSettings method), [1] (BaseModel method), [1], [2] (ConstantModel method), [1], [2] (GenericModel method), [1], [2] (IndividualParameters method), [1] (Leaspy method), [1] (LMEModel method), [1], [2] (MultivariateModel method), [1], [2] (MultivariateParallelModel method), [1], [2] (UnivariateModel method), [1], [2] save_individual_parameters_csv() (Result method) save_individual_parameters_json() (Result method) save_individual_parameters_torch() (Result method) save_model_parameters_convergence() (FitOutputManager method) save_realizations() (FitOutputManager method) scale_dimension (AbstractGaussianNoiseModel attribute), [1] (GaussianDiagonalNoiseModel attribute), [1] (GaussianScalarNoiseModel attribute), [1]

ScipyMinimize (class in leaspy.algo.personalize.scipy_minimize), [1] set_autograd() (AbstractRealization method), [1], [2] (IndividualRealization method), [1], [2] (PopulationRealization method), [1], [2] set_default_validate_args() (MultinomialDistribution static method) set_logs() (AlgorithmSettings method), [1] set_output_manager() (AbstractAlgo method), [1] (AbstractFitAlgo method), [1] (AbstractFitMCMC method), [1] (AbstractMCMCPersonalizeAlgo method) (AbstractPersonalizeAlgo method), [1] (ConstantPredictionAlgorithm method), [1] (LMEFitAlgorithm method), [1] (LMEPersonalizeAlgorithm method), [1] (MeanReal method) (ModeReal method) (ScipyMinimize method), [1] (SimulationAlgorithm method), [1] (TensorMCMCSAEM method), [1] set_palette() (Plotting method) set_tensor_realizations_element() (AbstractRealization method), [1], [2] (IndividualRealization method), [1], [2] (PopulationRealization method), [1], [2] shape_acceptation (AbstractIndividualSampler property), [1], [2] (AbstractPopulationGibbsSampler property) (AbstractPopulationSampler property), [1], [2] (AbstractSampler property), [1], [2] (GibbsSamplerMixin property) (IndividualGibbsSampler property), [1], [2] (PopulationFastGibbsSampler property), [1], [2] (PopulationGibbsSampler property), [1], [2] (PopulationMetropolisHastingsSampler property), [1], [2] shape_adapted_std (AbstractPopulationGibbsSampler property) (GibbsSamplerMixin property) (IndividualGibbsSampler property), [1], [2] (PopulationFastGibbsSampler property), [1], [2] (PopulationGibbsSampler property), [1], [2] (PopulationMetropolisHastingsSampler property), [1], [2] simulate() (Leaspy method), [1] SimulationAlgorithm (class in leaspy.algo.simulate.simulate), [1] source_dimension (MultivariateModel attribute) (UnivariateModel attribute), [1] sources space shifts spatial effects STD_SCALE_FACTOR (AbstractPopulationGibbsSampler attribute) (GibbsSamplerMixin attribute) (IndividualGibbsSampler attribute), [1] (PopulationFastGibbsSampler attribute), [1] (PopulationGibbsSampler attribute), [1] (PopulationMetropolisHastingsSampler attribute), [1] stddev (MultinomialDistribution property) subset() (IndividualParameters method), [1] SUBTYPES_SUFFIXES (MultivariateModel attribute), [1] (UnivariateModel attribute), [1] sufficient statistics sufficient_statistics (AbstractFitMCMC attribute) (TensorMCMCSAEM attribute) suffixed_method() (in module leaspy.utils.subtypes) support (MultinomialDistribution property)

T

temperature (MeanReal attribute) (ModeReal attribute) (TensorMCMCSAEM attribute) temperature_inv (MeanReal attribute) (ModeReal attribute) (TensorMCMCSAEM attribute) tensor (AbstractRealization property), [1] (IndividualRealization property), [1] (PopulationRealization property), [1] tensor_to_list() (in module leaspy.models.utilities) TensorMCMCSAEM (class in leaspy.algo.fit.tensor_mcmcsaem), [1] tensors (CollectionRealization property), [1] (DictRealizations property), [1] tensors_dict (CollectionRealization property), [1] (DictRealizations property), [1] time_reparametrization() (AbstractModel static method), [1], [2] (AbstractMultivariateModel static method), [1], [2] (MultivariateModel static method), [1], [2] (MultivariateParallelModel static method), [1], [2] (UnivariateModel static method), [1], [2] time_rounding_digits (CSVDataReader attribute) (DataframeDataReader attribute) to_dataframe() (Data method), [1] (IndividualParameters method), [1]

to_dict() (AbstractGaussianNoiseModel method), [1], [2] (AbstractModel method), [1], [2] (AbstractMultivariateModel method), [1], [2] (AbstractOrdinalNoiseModel method), [1], [2] (AbstractRealization method), [1], [2] (BaseNoiseModel method), [1], [2] (BernoulliFamily method) (BernoulliNoiseModel method), [1], [2] (DistributionFamily method), [1], [2] (GaussianDiagonalNoiseModel method), [1], [2] (GaussianFamily method) (GaussianScalarNoiseModel method), [1], [2] (IndividualRealization method), [1], [2] (MultivariateModel method), [1], [2] (MultivariateParallelModel method), [1], [2] (NoNoise method) (OrdinalFamily method) (OrdinalNoiseModel method), [1], [2] (OrdinalRankingFamily method) (OrdinalRankingNoiseModel method), [1], [2] (PopulationRealization method), [1], [2] (UnivariateModel method), [1], [2] to_pandas() (Dataset method), [1] to_pytorch() (IndividualParameters method), [1] type (Leaspy property)

U

UnivariateModel (class in leaspy.models), [1] (class in leaspy.models.univariate) unset_autograd() (AbstractRealization method), [1], [2] (IndividualRealization method), [1], [2] (PopulationRealization method), [1], [2] update() (AbstractAttributes method), [1] (AbstractManifoldModelAttributes method), [1] (LinearAttributes method), [1] (LogisticAttributes method), [1] (LogisticOrdinalAttributes method) (LogisticParallelAttributes method), [1] update_MCMC_toolbox() (AbstractMultivariateModel method), [1], [2] (MultivariateModel method), [1], [2] (MultivariateParallelModel method), [1], [2] (UnivariateModel method), [1], [2] update_model_parameters_burn_in() (AbstractModel method), [1], [2] (AbstractMultivariateModel method), [1], [2] (MultivariateModel method), [1], [2] (MultivariateParallelModel method), [1], [2] (UnivariateModel method), [1], [2] update_model_parameters_normal() (AbstractModel method), [1], [2] (AbstractMultivariateModel method), [1], [2] (MultivariateModel method), [1], [2] (MultivariateParallelModel method), [1], [2] (UnivariateModel method), [1], [2] update_ordinal_population_random_variable_information() (AbstractMultivariateModel method), [1], [2] (MultivariateModel method), [1], [2] (MultivariateParallelModel method), [1], [2] (OrdinalModelMixin method) (UnivariateModel method), [1], [2] update_parameters() (AbstractGaussianNoiseModel method), [1], [2] (AbstractOrdinalNoiseModel method), [1], [2] (BaseNoiseModel method), [1], [2] (BernoulliFamily method) (BernoulliNoiseModel method), [1], [2] (DistributionFamily method), [1], [2] (GaussianDiagonalNoiseModel method), [1], [2] (GaussianFamily method) (GaussianScalarNoiseModel method), [1], [2] (NoNoise method) (OrdinalFamily method) (OrdinalNoiseModel method), [1], [2] (OrdinalRankingFamily method) (OrdinalRankingNoiseModel method), [1], [2]

update_parameters_burn_in() (AbstractModel method), [1], [2] (AbstractMultivariateModel method), [1], [2] (MultivariateModel method), [1], [2] (MultivariateParallelModel method), [1], [2] (UnivariateModel method), [1], [2] update_parameters_from_predictions() (AbstractGaussianNoiseModel method), [1], [2] (AbstractOrdinalNoiseModel method), [1], [2] (BaseNoiseModel method), [1], [2] (BernoulliNoiseModel method), [1], [2] (GaussianDiagonalNoiseModel method), [1], [2] (GaussianScalarNoiseModel method), [1], [2] (OrdinalNoiseModel method), [1], [2] (OrdinalRankingNoiseModel method), [1], [2] update_parameters_from_sufficient_statistics() (AbstractGaussianNoiseModel method), [1], [2] (AbstractOrdinalNoiseModel method), [1], [2] (BaseNoiseModel method), [1], [2] (BernoulliNoiseModel method), [1], [2] (GaussianDiagonalNoiseModel method), [1], [2] (GaussianScalarNoiseModel method), [1], [2] (OrdinalNoiseModel method), [1], [2] (OrdinalRankingNoiseModel method), [1], [2] update_parameters_normal() (AbstractModel method), [1], [2] (AbstractMultivariateModel method), [1], [2] (MultivariateModel method), [1], [2] (MultivariateParallelModel method), [1], [2] (UnivariateModel method), [1], [2]

V

VALID_IO_EXTENSIONS (IndividualParameters attribute) validate() (AbstractGaussianNoiseModel method), [1], [2] (AbstractOrdinalNoiseModel method), [1], [2] (BaseNoiseModel method), [1], [2] (BernoulliFamily method) (BernoulliNoiseModel method), [1], [2] (DistributionFamily method), [1], [2] (GaussianDiagonalNoiseModel method), [1], [2] (GaussianFamily method) (GaussianScalarNoiseModel method), [1], [2] (NoNoise method) (OrdinalFamily method) (OrdinalNoiseModel method), [1], [2] (OrdinalRankingFamily method) (OrdinalRankingNoiseModel method), [1], [2] validate_compatibility_of_dataset() (AbstractModel method), [1], [2] (AbstractMultivariateModel method), [1], [2] (BaseModel method), [1], [2] (ConstantModel method), [1], [2] (GenericModel method), [1], [2] (LMEModel method), [1], [2] (MultivariateModel method), [1], [2] (MultivariateParallelModel method), [1], [2] (UnivariateModel method), [1], [2]

validate_scale() (AbstractGaussianNoiseModel method), [1], [2] (AbstractPopulationGibbsSampler method) (GaussianDiagonalNoiseModel method), [1], [2] (GaussianFamily method) (GaussianScalarNoiseModel method), [1], [2] (GibbsSamplerMixin method) (IndividualGibbsSampler method), [1], [2] (PopulationFastGibbsSampler method), [1], [2] (PopulationGibbsSampler method), [1], [2] (PopulationMetropolisHastingsSampler method), [1], [2] value_to_tensor() (in module leaspy.models.noise_models.base) VariableType (class in leaspy.io.realizations), [1] (class in leaspy.io.realizations.factory) variance (MultinomialDistribution property)

W

with_traceback() (LeaspyAlgoInputError method) (LeaspyConvergenceError method) (LeaspyDataInputError method) (LeaspyException method) (LeaspyIndividualParamsInputError method) (LeaspyInputError method) (LeaspyModelInputError method) (LeaspyTypeError method)