Package: SamplerCompare 1.3.4.9001

Madeleine Thompson

SamplerCompare: A Framework for Comparing the Performance of MCMC Samplers

A framework for running sets of MCMC samplers on sets of distributions with a variety of tuning parameters, along with plotting functions to visualize the results of those simulations. Compatibility updates by Renova.

Authors:Madeleine Thompson, except dchud.f and dchdd.f, which were written by G. W. Stewart.

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manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
SamplerCompare/json (API)

# Install 'SamplerCompare' in R:
install.packages('SamplerCompare', repos = c('https://renova-r.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/renova-r/samplercompare/issues

On CRAN:

Conda:

3.38 score 24 scripts 169 downloads 37 exports 1 dependencies

Last updated from:b5835942cf (on renova-1.3.4.9001). Checks:15 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK104
linux-devel-x86_64OK154
source / vignettesOK184
linux-release-arm64OK100
linux-release-x86_64OK108
macos-release-arm64OK94
macos-release-x86_64OK140
macos-oldrel-arm64OK101
macos-oldrel-x86_64OK142
windows-devel-arm64OK348
windows-devel-x86_64OK171
windows-release-arm64OK315
windows-release-x86_64OK161
windows-oldrel-x86_64OK190
wasm-releaseOK103

Exports:adaptive.metropolis.samplear.actarms.samplechddcheat.oblique.hyperrect.samplecheat.univar.eigen.samplecheck.dist.gradientchudcompare.samplerscomparison.plotcompounded.samplercov.match.samplefunnel.disthyperrectangle.sampleinterval.slice.samplemake.c.distmake.cone.distmake.distmake.gaussianmake.multimodal.distmake.mv.gamma.distmultivariate.metropolis.sampleN2weakcor.distN4negcor.distN4poscor.distnograd.hyperrectangle.samplenonadaptive.crumb.sampleoblique.hyperrect.sampleraw.symbolschools.distshrinking.rank.samplesimulation.resultstepout.slice.sampletwonormunivar.eigen.sampleunivar.metropolis.samplewrap.c.sampler

Dependencies:mvtnorm

Introduction to SamplerCompare
Purpose of package | Installation and documentation | Simulations with included samplers and distributions | Visualizing results | Defining a sampler | Defining a distribution | Comparing user-defined distributions and samplers | Limitations
Rendered fromsc-intro.Rnwusingutils::Sweave

Last update: 2026-11-13
Started: 2026-11-13

R/C Glue in SamplerCompare
Rendered fromglue.Rnwusingutils::Sweave

Last update: 2026-11-13
Started: 2026-11-13

Readme and manuals

Help Manual

Help pageTopics
Adaptive Metropolisadaptive.metropolis.sample
Compute the autocorrelation time of a chainar.act
Adaptive Rejection Metropolis Samplerarms.sample
Test a gradient functioncheck.dist.gradient
Cholesky Update/Downdatechdd chud
Compare MCMC samplers on distributionscompare.samplers
Plot the results of compare.samplerscomparison.plot
Build a sampler from transition functionscompounded.sampler
Sample with covariance-matching slice samplingcov.match.sample
Funnel distribution objectfunnel.dist
Multivariate slice samplershyperrectangle.sample nograd.hyperrectangle.sample
Define a probability distribution object with C log-densitymake.c.dist
Create a cone distribution objectmake.cone.dist
Define a probability distribution objectmake.dist
Gaussian distribution objectsmake.gaussian N2weakcor.dist N4negcor.dist N4poscor.dist
Create a distribution object for a random mixture of Gaussiansmake.multimodal.dist
Create a distribution object for a set of uncorrelated Gamma distributionsmake.mv.gamma.dist
Metropolis samplersmultivariate.metropolis.sample univar.metropolis.sample
Sample with nonadaptive-crumb slice samplingnonadaptive.crumb.sample
Eigendecomposition-based hyperrectangle methodcheat.oblique.hyperrect.sample oblique.hyperrect.sample
Locate a symbolraw.symbol
A class representing a probability distributionscdist-class
Eight schools distribution objectschools.dist
Sample with shrinking-rank slice samplingshrinking.rank.sample
Summarize one MCMC chainsimulation.result
Univariate slice samplersinterval.slice.sample stepout.slice.sample
Euclidean norm of a vectortwonorm
Eigendecomposition-based slice samplerscheat.univar.eigen.sample univar.eigen.sample
Create an R stub function for a sampler implemented in Cwrap.c.sampler