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SamplerCompare (version 1.3.4)

A Framework for Comparing the Performance of MCMC Samplers

Description

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.

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Version

Install

install.packages('SamplerCompare')

Monthly Downloads

55

Version

1.3.4

License

GPL-2

Maintainer

Madeleine Thompson

Last Published

April 24th, 2023

Functions in SamplerCompare (1.3.4)

make.mv.gamma.dist

Create a distribution object for a set of uncorrelated Gamma distributions

Euclidean norm of a vector

stepout.slice.sample

Univariate slice samplers

univar.eigen.sample

Eigendecomposition-based slice samplers

simulation.result

Summarize one MCMC chain

Eight schools distribution object

Create an R stub function for a sampler implemented in C

shrinking.rank.sample

Sample with shrinking-rank slice sampling

Locate a symbol

oblique.hyperrect.sample

Eigendecomposition-based hyperrectangle method

check.dist.gradient

Test a gradient function

Adaptive Rejection Metropolis Sampler

Cholesky Update/Downdate

compounded.sampler

Build a sampler from transition functions

compare.samplers

Compare MCMC samplers on distributions

A class representing a probability distribution

Compute the autocorrelation time of a chain

adaptive.metropolis.sample

Adaptive Metropolis

cov.match.sample

Sample with covariance-matching slice sampling

comparison.plot

Plot the results of compare.samplers

Define a probability distribution object with C log-density

Create a cone distribution object

Gaussian distribution objects

nonadaptive.crumb.sample

Sample with nonadaptive-crumb slice sampling

hyperrectangle.sample

Multivariate slice samplers

multivariate.metropolis.sample

Metropolis samplers

make.multimodal.dist

Create a distribution object for a random mixture of Gaussians

Define a probability distribution object

Funnel distribution object