chain_state: Construct a new chain state.

In rmcmc: Robust Markov Chain Monte Carlo Methods

Construct a new chain state.

Description

The chain state object provides cached access to target distribution log density and its gradient.

Usage

chain_state(position, momentum = NULL)

Arguments

position	Position component of chain state.
momentum	Momentum component of chain state. Optional.

Value

New chain state object. A list with entries

• position: A zero-argument function to evaluate position vector.

• momentum: A zero-argument function to evaluate momentum vector.

• dimension: A zero-argument function evaluate dimension of position and momentum vectors.

• update: A function accepting arguments position and momentum for updating the value of one or both of these state components.

• copy: A function for creating a copy of the state object including any cached values.

• log_density: A function accepting argument target_distribution for evaluating the log density of the target distribution at the current state, with caching of the value to avoid recomputation on subsequent calls.

• gradient_log_density: A function accepting argument target_distribution for evaluating the gradient of the log density of the target distribution at the current state, with caching of the value to avoid recomputation on subsequent calls.

Examples

state <- chain_state(c(0.1, -0.5))
target_distribution <- list(
  log_density = function(x) -sum(x^2) / 2,
  gradient_log_density = function(x) -x
)
state$gradient_log_density(target_distribution)

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