Combinators for creating transition kernels from other kernels or things that are not quite transition kernels.
Provides Markov transition kernels for a few common MCMC techniques
Given an initial state and an arbitrary Markov transition, return a sampler for doing mcmc
Performs Metropolis distributions on a random variable.
Performs Metropolis distributions on a random variable. Note this is not Metropolis-Hastings
The initial parameter
the symmetric proposal distribution generator
the distribution we want to sample from
Performs Metropolis-Hastings distributions on a random variable.
Performs Metropolis-Hastings distributions on a random variable.
The initial parameter
the proposal distribution generator
the distribution we want to sample from
Creates a slice sampler for a function.
Creates a slice sampler for a function. logMeasure should be an (unnormalized) log pdf.
guess
an unnormalized probability measure
a slice sampler
Provides methods for doing MCMC.