sample_metropolis_hastings: Sample from Metropolis-Hastings kernel.

In rmcmc: Robust Markov Chain Monte Carlo Methods

Sample from Metropolis-Hastings kernel.

Description

Sample from Metropolis-Hastings kernel.

Usage

sample_metropolis_hastings(
  state,
  target_distribution,
  proposal,
  sample_uniform = stats::runif
)

Arguments

state	Current chain state.
target_distribution	Target stationary distribution for chain. A list with named entries log_density and gradient_log_density corresponding to respectively functions for evaluating the logarithm of the (potentially unnormalized) density of the target distribution and its gradient. As an alternative to gradient_log_density an entry value_and_gradient_log_density may instead be provided which is a function returning both the value and gradient of the logarithm of the (unnormalized) density of the target distribution as a list under the names value and gradient respectively.
proposal	Proposal distribution object. Must define entries sample, a function to generate sample from proposal distribution given current chain state and log_density_ratio, a function to compute log density ratio for proposal for a given pair of current and proposed chain states.
sample_uniform	Function which generates a random vector from standard uniform distribution given an integer size.

Value

List with named entries

• state: corresponding to new chain state,

• proposed_state: corresponding to proposed chain state,

• statistics: a list with named entries for statistics of transition, here this consisting of a named entry accept_prob for the Metropolis acceptance probability.

rmcmc documentation built on April 3, 2025, 5:27 p.m.