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Guides
Model building
Overview
Build your first model
Fit and predict
Inspect a model
Transform parameters
Change a model
Combine models
Evaluate model states
Predict quantities
Simulate responses
Use distributions
Optimization
Overview
Fit your first model
Fit two data groups
Monitor a fit
Choose optimizers
Split data
Create minibatches
Scale the loss
Sample with weights
Pause and resume
Migrate optim_flat
MCMC sampling
Overview
First posterior
NUTS and Gibbs
Choose kernels
Choose initial values
Configure sampling
Check diagnostics
Use posterior draws
Compare predictions
Use the engine
Reproducibility
Custom kernels
Example library
Overview
GEV regression
Compare samplers
Variable selection with PyMC
Correct measurement error
Models
Model
Model.add()
Model.convert_position()
Model.copy()
Model.copy_nodes_and_vars()
Model.copy_vars()
Model.diagnose()
Model.drop_singletons()
Model.extract_position()
Model.groups()
Model.join()
Model.join_by_all()
Model.modify_names()
Model.node_parental_subgraph()
Model.parental_submodel()
Model.plot()
Model.plot_nodes()
Model.plot_vars()
Model.pop_nodes_and_vars()
Model.pop_vars()
Model.predict()
Model.prefix_names()
Model.rebuild_graph()
Model.replace()
Model.sample()
Model.set_seed()
Model.simulate()
Model.update()
Model.update_graph()
Model.update_state()
Model.var_parental_subgraph()
Model.auto_update
Model.graph_outdated
Model.locked
Model.log_lik
Model.log_prior
Model.log_prob
Model.model_nodes
Model.node_graph
Model.nodes
Model.observed
Model.parameters
Model.seed_nodes_and_vars
Model.state
Model.var_graph
Model.vars
Model.update_graph_lazily
Var
Var.all_input_nodes()
Var.all_input_vars()
Var.all_output_nodes()
Var.all_output_vars()
Var.biject()
Var.convert_value()
Var.diagnose()
Var.ensure_name()
Var.get_inference()
Var.new_calc()
Var.new_obs()
Var.new_param()
Var.new_value()
Var.plot()
Var.plot_nodes()
Var.plot_vars()
Var.predict()
Var.sample()
Var.transform()
Var.update()
Var.inference
Var.info
Var.auto_transform
Var.bijected_var
Var.dist_node
Var.groups
Var.has_bijected_var
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
Nodes
Overview
Calc
Node
Value
PIT()
TransientCalc
TransientDist
TransientIdentity
TransientNode
InputGroup
GraphBuilder
Log densities
Overview
log_prob_pointwise()
LogProb
FlatLogProb
Distributions
Overview
GaussianCopula
MultivariateNormalDegenerate
Splines
Overview
basis_matrix()
equidistant_knots()
pspline_penalty()
MCMC
LieselMCMC
LieselMCMC.get_engine_builder()
LieselMCMC.get_jitter_functions()
LieselMCMC.get_kernel_groups()
LieselMCMC.get_kernel_list()
LieselMCMC.get_spec()
LieselMCMC.run_for_epochs()
LieselMCMC.validate_inference_specs()
LieselMCMC.which
LieselMCMC.model
MCMCSpec
MCMCSpec.apply_jitter()
MCMCSpec.jitter_dist
MCMCSpec.jitter_method
MCMCSpec.kernel_group
MCMCSpec.order
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.minimize_transition_infos
EngineBuilder.positions_excluded
EngineBuilder.positions_included
EngineBuilder.show_progress
EngineBuilder.store_kernel_states
Engine
Engine.append_epoch()
Engine.get_results()
Engine.is_sampling_done()
Engine.sample_all_epochs()
Engine.sample_next_epoch()
Engine.current_epoch
Kernels
Overview
IWLSKernel
NUTSKernel
HMCKernel
RWKernel
MHKernel
MHProposal
GibbsKernel
Interfaces
Overview
LieselInterface
DictInterface
DataclassInterface
NamedTupleInterface
Advanced
Overview
mh_step()
liesel.goose.da
liesel.goose.mm
EpochConfig
EpochState
EpochType
KernelState
ModelState
Kernel
TransitionInfo
TuningInfo
DefaultTransitionInfo
DefaultTuningInfo
TransitionMixin
TransitionOutcome
TuningOutcome
WarmupOutcome
ModelMixin
MCMC results
SamplingResults
SamplingResults.get_adaptation_samples()
SamplingResults.get_error_log()
SamplingResults.get_kernels_by_pos_key()
SamplingResults.get_pos_keys_by_kernels()
SamplingResults.get_posterior_acceptance_probabilities()
SamplingResults.get_posterior_position_moved()
SamplingResults.get_posterior_samples()
SamplingResults.get_posterior_transition_infos()
SamplingResults.get_samples()
SamplingResults.get_tuning_times()
SamplingResults.get_warmup_acceptance_probabilities()
SamplingResults.get_warmup_kernel_states()
SamplingResults.get_warmup_position_moved()
SamplingResults.get_warmup_samples()
SamplingResults.get_warmup_transition_infos()
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.acceptance_prob_df()
Summary.aggregate_diagnostics()
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
Summary.pos_keys_by_kernels_df
SamplesSummary
SamplesSummary.aggregate_diagnostics()
SamplesSummary.from_array()
SamplesSummary.to_dataframe()
SamplesSummary.config
SamplesSummary.per_chain
SamplesSummary.quantities
SamplesSummary.sample_info
loo()
Plots
Overview
plot_trace()
plot_cor()
plot_pairs()
plot_scatter()
plot_density()
plot_param()
Optimization
LieselOptim
LieselOptim.build_engine()
LieselOptim.fit()
LieselOptim.batches
LieselOptim.loss
LieselOptim.loss_monitor
LieselOptim.model
LieselOptim.optimizers
LieselOptim.progress_update_every
LieselOptim.save_position_history
LieselOptim.seed
LieselOptim.show_progress
LieselOptim.show_step_progress
LieselOptim.split
LieselOptim.step_progress_update_every
LieselOptim.stopper
OptimEngine
OptimEngine.fit()
OptimEngine.debug_nans
OptimEngine.position_keys
OptimEngine.progress_update_every
OptimEngine.prune_history
OptimEngine.save_position_history
OptimEngine.show_progress
OptimEngine.show_step_progress
OptimEngine.split
OptimEngine.step_progress_update_every
OptimEngine.loss
OptimEngine.batches
OptimEngine.optimizers
OptimEngine.stopper
OptimEngine.seed
OptimEngine.initial_state
OptimEngine.loss_monitor
OptimCheckpoint
OptimCheckpoint.load()
OptimCheckpoint.save()
OptimCheckpoint.duration
OptimCheckpoint.history
OptimCheckpoint.n_epochs
OptimCheckpoint.versions
OptimHistory
OptimHistory.from_epochs()
OptimHistory.init_position_history()
OptimHistory.loss_df()
OptimHistory.position_df()
OptimHistory.update_position_history()
OptimHistory.loss_train
OptimHistory.loss_monitor
OptimHistory.position
OptimResult
OptimResult.plot_loss()
OptimResult.plot_loss_overview()
OptimResult.plot_params()
OptimResult.checkpoint
OptimResult.nan_debug
OptimResult.position_final
OptimResult.position_min_monitor
OptimResult.status
OptimResult.history
OptimResult.n_epochs
OptimResult.min_monitor_epoch
OptimResult.monitor_source
OptimResult.patience
OptimResult.duration
OptimNaNDebugInfo
OptimNaNDebugInfo.optimizer()
OptimNaNDebugInfo.reproduce_loss()
OptimNaNDebugInfo.reproduce_step()
OptimNaNDebugInfo.position
OptimNaNDebugInfo.kind
OptimNaNDebugInfo.epoch
OptimNaNDebugInfo.batch
OptimNaNDebugInfo.obs_batch
OptimNaNDebugInfo.last_non_nan_position
OptimNaNDebugInfo.nan_position
OptimNaNDebugInfo.loss
OptimNaNDebugInfo.optimizer_index
OptimNaNDebugInfo.optimizer_identifier
OptimNaNDebugInfo.optimizer_position_keys
OptimNaNDebugInfo.reproduction_position
OptimNaNDebugInfo.reproduction_carry
Stopper
Stopper.continue_()
Stopper.stop_early()
Stopper.stop_now()
Stopper.which_best_in_recent_history()
Stopper.atol
Stopper.max_iter
Stopper.min_epochs
Stopper.rtol
Stopper.epochs
Stopper.patience
EmaTrainLossMonitor
EmaTrainLossMonitor.from_half_life()
EmaTrainLossMonitor.effective_window
liesel.optim.LossMonitor
Losses
Overview
Loss
LossMixin
NegLogProbLoss
Optimizers
Overview
Optimizer
OptimizerLike
LBFGS
Data
Overview
Batches
BatchManager
Split
SplitManager
PositionSplit
PositionSplitManager
Experimental
liesel.experimental.arviz
to_arviz_inference_data()
liesel.experimental.pymc
PyMCInterface
Deprecated
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
.rst
.pdf
System Settings
Light
Dark
LieselOptim.loss
Contents
LieselOptim.loss
LieselOptim.loss
#
LieselOptim.
loss
:
Loss
#
Custom loss.
Contents
LieselOptim.loss
