Skip to main content

Ctrl+K

Guides

Model building
Optimization
MCMC sampling
Example library

Models

Model
Var
Dist

Nodes
- Overview
- Calc
- Node
- Value
- PIT()
- TransientCalc
- TransientDist
- TransientIdentity
- TransientNode
- InputGroup
- GraphBuilder
Log densities
Distributions
Splines

MCMC

LieselMCMC
MCMCSpec
EngineBuilder
Engine

Kernels
- Overview
- IWLSKernel
- NUTSKernel
- HMCKernel
- RWKernel
- MHKernel
- MHProposal
- GibbsKernel
Interfaces
Advanced

MCMC results

SamplingResults
Summary
SamplesSummary
loo()

Plots

Optimization

LieselOptim
OptimEngine
OptimCheckpoint
OptimHistory
OptimResult
OptimNaNDebugInfo
Stopper
EmaTrainLossMonitor
- EmaTrainLossMonitor.from_half_life()
- EmaTrainLossMonitor.effective_window
liesel.optim.LossMonitor

Losses
Optimizers
Data

Experimental

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

Deprecated

optim_flat()
Stopper
history_to_df()
OptimResult

.rst

SamplesSummary.per_chain

Contents

SamplesSummary.per_chain

SamplesSummary.per_chain#

SamplesSummary.per_chain: bool#: Whether summaries are computed separately for each chain.

previous

SamplesSummary.config

next

SamplesSummary.quantities

Contents

SamplesSummary.per_chain

By Liesel Developers

© Copyright 2022-2026, Liesel Developers.