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Guides

  • Tutorials
    • Linear regression
    • Parameter transformations
    • Location-scale regression
    • GEV responses
    • Comparing samplers
    • Reproducibility
    • PyMC and Liesel: Spike and Slab

Model Basics

  • Model
    • Model.copy_nodes_and_vars()
    • Model.extract_position()
    • Model.groups()
    • Model.node_parental_subgraph()
    • Model.parental_submodel()
    • Model.plot_nodes()
    • Model.plot_vars()
    • Model.pop_nodes_and_vars()
    • Model.predict()
    • Model.sample()
    • Model.set_seed()
    • Model.simulate()
    • Model.update()
    • Model.update_state()
    • Model.var_parental_subgraph()
    • Model.auto_update
    • Model.log_lik
    • Model.log_prior
    • Model.log_prob
    • Model.node_graph
    • Model.nodes
    • Model.observed
    • Model.parameters
    • Model.state
    • Model.var_graph
    • Model.vars
  • Var
    • Var.all_input_nodes()
    • Var.all_input_vars()
    • Var.all_output_nodes()
    • Var.all_output_vars()
    • Var.biject()
    • Var.get_inference()
    • Var.new_calc()
    • Var.new_obs()
    • Var.new_param()
    • Var.new_value()
    • Var.plot_nodes()
    • Var.plot_vars()
    • Var.predict()
    • Var.sample()
    • Var.transform()
    • Var.update()
    • Var.info
    • Var.inference
    • Var.auto_transform
    • Var.bijected_var
    • Var.dist_node
    • Var.groups
    • Var.has_dist
    • Var.log_prob
    • Var.model
    • Var.name
    • Var.nodes
    • Var.observed
    • Var.parameter
    • Var.role
    • Var.strong
    • Var.value
    • Var.value_node
    • Var.var_value_node
    • Var.weak
  • Dist
    • Dist.all_input_nodes()
    • Dist.biject_parameters()
    • Dist.find_default_parameter_bijectors()
    • Dist.init_dist()
    • Dist.update()
    • Dist.at
    • Dist.distribution
    • Dist.log_prob
    • Dist.per_obs
    • Dist.monitor

MCMC Setup

  • LieselMCMC
    • LieselMCMC.get_engine_builder()
    • LieselMCMC.get_jitter_functions()
    • LieselMCMC.get_kernel_groups()
    • LieselMCMC.get_kernel_list()
    • LieselMCMC.get_spec()
    • LieselMCMC.which
    • LieselMCMC.model
  • MCMCSpec
    • MCMCSpec.apply_jitter()
    • MCMCSpec.jitter_dist
    • MCMCSpec.jitter_method
    • MCMCSpec.kernel_group
    • MCMCSpec.kernel
    • MCMCSpec.kernel_kwargs
  • EngineBuilder
    • EngineBuilder.add_adaptation()
    • EngineBuilder.add_burnin()
    • EngineBuilder.add_kernel()
    • EngineBuilder.add_posterior()
    • EngineBuilder.add_quantity_generator()
    • EngineBuilder.append_epochs()
    • EngineBuilder.build()
    • EngineBuilder.set_duration()
    • EngineBuilder.set_duration_simple()
    • EngineBuilder.set_engine_seed()
    • EngineBuilder.set_epochs()
    • EngineBuilder.set_initial_values()
    • EngineBuilder.set_jitter_fns()
    • EngineBuilder.set_model()
    • EngineBuilder.engine_seed
    • EngineBuilder.epochs
    • EngineBuilder.jitter_fns
    • EngineBuilder.kernels
    • EngineBuilder.model_state
    • EngineBuilder.quantity_generators
    • EngineBuilder.show_progress
    • EngineBuilder.positions_included
    • EngineBuilder.positions_excluded
  • Engine
    • Engine.append_epoch()
    • Engine.get_results()
    • Engine.is_sampling_done()
    • Engine.sample_all_epochs()
    • Engine.sample_next_epoch()
    • Engine.current_epoch
  • EpochConfig
    • EpochConfig.to_state()
    • EpochConfig.type
    • EpochConfig.duration
    • EpochConfig.thinning
    • EpochConfig.optional

MCMC Kernels

  • IWLSKernel
    • IWLSKernel.end_epoch()
    • IWLSKernel.end_warmup()
    • IWLSKernel.init_state()
    • IWLSKernel.start_epoch()
    • IWLSKernel.tune()
    • IWLSKernel.untuned()
    • IWLSKernel.error_book
    • IWLSKernel.fallback_chol_info
    • IWLSKernel.identifier
    • IWLSKernel.needs_history
    • IWLSKernel.position_keys
  • NUTSKernel
    • NUTSKernel.end_epoch()
    • NUTSKernel.end_warmup()
    • NUTSKernel.init_state()
    • NUTSKernel.start_epoch()
    • NUTSKernel.error_book
    • NUTSKernel.identifier
    • NUTSKernel.needs_history
    • NUTSKernel.position_keys
  • HMCKernel
    • HMCKernel.end_epoch()
    • HMCKernel.end_warmup()
    • HMCKernel.init_state()
    • HMCKernel.start_epoch()
    • HMCKernel.error_book
    • HMCKernel.identifier
    • HMCKernel.needs_history
    • HMCKernel.position_keys
  • RWKernel
    • RWKernel.end_epoch()
    • RWKernel.end_warmup()
    • RWKernel.init_state()
    • RWKernel.start_epoch()
    • RWKernel.tune()
    • RWKernel.error_book
    • RWKernel.identifier
    • RWKernel.needs_history
    • RWKernel.position_keys
  • MHKernel
    • MHKernel.end_epoch()
    • MHKernel.end_warmup()
    • MHKernel.init_state()
    • MHKernel.start_epoch()
    • MHKernel.tune()
    • MHKernel.error_book
    • MHKernel.identifier
    • MHKernel.needs_history
    • MHKernel.position_keys
  • MHProposal
    • MHProposal.log_correction
    • MHProposal.position
  • GibbsKernel
    • GibbsKernel.end_epoch()
    • GibbsKernel.end_warmup()
    • GibbsKernel.init_state()
    • GibbsKernel.start_epoch()
    • GibbsKernel.transition()
    • GibbsKernel.tune()
    • GibbsKernel.error_book
    • GibbsKernel.identifier
    • GibbsKernel.needs_history
    • GibbsKernel.position_keys
  • Kernel
    • Kernel.end_epoch()
    • Kernel.end_warmup()
    • Kernel.has_model()
    • Kernel.init_state()
    • Kernel.set_model()
    • Kernel.start_epoch()
    • Kernel.transition()
    • Kernel.tune()
    • Kernel.identifier
    • Kernel.needs_history
    • Kernel.error_book
    • Kernel.position_keys

MCMC Results & Summary

  • SamplingResults
    • SamplingResults.get_adaptation_samples()
    • SamplingResults.get_error_log()
    • SamplingResults.get_kernels_by_pos_key()
    • SamplingResults.get_posterior_samples()
    • SamplingResults.get_posterior_transition_infos()
    • SamplingResults.get_samples()
    • SamplingResults.get_tuning_times()
    • SamplingResults.get_warmup_samples()
    • SamplingResults.pkl_load()
    • SamplingResults.pkl_save()
    • SamplingResults.positions
    • SamplingResults.transition_infos
    • SamplingResults.generated_quantities
    • SamplingResults.tuning_infos
    • SamplingResults.kernel_states
    • SamplingResults.full_model_states
    • SamplingResults.kernel_classes
    • SamplingResults.kernels_by_pos_key
  • Summary
    • Summary.error_df()
    • Summary.to_dataframe()
    • Summary.per_chain
    • Summary.quantities
    • Summary.config
    • Summary.sample_info
    • Summary.error_summary
    • Summary.kernels_by_pos_key
    • Summary.liesel_version
  • SamplesSummary
    • SamplesSummary.from_array()
    • SamplesSummary.to_dataframe()
    • SamplesSummary.config

Plots

  • plot_trace()
  • plot_cor()
  • plot_pairs()
  • plot_scatter()
  • plot_density()
  • plot_param()

Optimization

  • optim_flat()
  • Stopper
    • Stopper.continue_()
    • Stopper.stop_early()
    • Stopper.stop_now()
    • Stopper.which_best_in_recent_history()
    • Stopper.atol
    • Stopper.rtol
    • Stopper.max_iter
    • Stopper.patience
  • history_to_df()
  • OptimResult
    • OptimResult.model_state
    • OptimResult.position
    • OptimResult.iteration
    • OptimResult.iteration_best
    • OptimResult.history
    • OptimResult.max_iter
    • OptimResult.n_train
    • OptimResult.n_validation

Model (Advanced)

  • Calc
    • Calc.update()
    • Calc.function
    • Calc.monitor
  • Node
    • Node.add_inputs()
    • Node.all_input_nodes()
    • Node.all_output_nodes()
    • Node.clear_state()
    • Node.flag_outdated()
    • Node.set_inputs()
    • Node.update()
    • Node.groups
    • Node.inputs
    • Node.kwinputs
    • Node.model
    • Node.name
    • Node.needs_seed
    • Node.outdated
    • Node.outputs
    • Node.state
    • Node.value
    • Node.var
    • Node.monitor
  • Value
    • Value.flag_outdated()
    • Value.update()
    • Value.outdated
    • Value.value
    • Value.monitor
  • PIT()
  • TransientCalc
    • TransientCalc.value
    • TransientCalc.monitor
  • TransientDist
    • TransientDist.value
    • TransientDist.monitor
  • TransientIdentity
    • TransientIdentity.monitor
  • TransientNode
    • TransientNode.update()
    • TransientNode.outdated
    • TransientNode.state
    • TransientNode.value
    • TransientNode.monitor
  • InputGroup
    • InputGroup.value
    • InputGroup.monitor
  • GraphBuilder
    • GraphBuilder.add()
    • GraphBuilder.add_groups()
    • GraphBuilder.build_model()
    • GraphBuilder.convert_dtype()
    • GraphBuilder.copy()
    • GraphBuilder.count_node_names()
    • GraphBuilder.count_var_names()
    • GraphBuilder.groups()
    • GraphBuilder.plot_nodes()
    • GraphBuilder.plot_vars()
    • GraphBuilder.rename()
    • GraphBuilder.rename_nodes()
    • GraphBuilder.rename_vars()
    • GraphBuilder.replace_node()
    • GraphBuilder.replace_var()
    • GraphBuilder.update()
    • GraphBuilder.log_lik_node
    • GraphBuilder.log_prior_node
    • GraphBuilder.log_prob_node
    • GraphBuilder.nodes
    • GraphBuilder.vars

Model Interfaces

  • LieselInterface
    • LieselInterface.extract_position()
    • LieselInterface.log_prob()
    • LieselInterface.update_state()
  • DictInterface
    • DictInterface.extract_position()
    • DictInterface.log_prob()
    • DictInterface.update_state()
  • NamedTupleInterface
    • NamedTupleInterface.extract_position()
    • NamedTupleInterface.log_prob()
    • NamedTupleInterface.update_state()

P-Splines

  • basis_matrix()
  • equidistant_knots()
  • pspline_penalty()
  • MultivariateNormalDegenerate
    • MultivariateNormalDegenerate.cross_entropy()
    • MultivariateNormalDegenerate.from_penalty()
    • MultivariateNormalDegenerate.from_penalty_smooth()
    • MultivariateNormalDegenerate.kl_divergence()
    • MultivariateNormalDegenerate.eig
    • MultivariateNormalDegenerate.loc
    • MultivariateNormalDegenerate.log_pdet
    • MultivariateNormalDegenerate.prec
    • MultivariateNormalDegenerate.rank

Experimental API

  • liesel.experimental
    • liesel.experimental.arviz
      • to_arviz_inference_data()
    • liesel.experimental.pymc
      • PyMCInterface

Python Module Index

l
 
l
- liesel
    liesel.experimental
    liesel.experimental.arviz
    liesel.experimental.pymc

By Hannes Riebl & Paul Wiemann

© Copyright 2022, Hannes Riebl & Paul Wiemann.