get_hmc_mcmc_result: Run Hamiltonian Monte Carlo to Get MCMC Sample Result

In catalytic: Tools for Applying Catalytic Priors in Statistical Modeling

Run Hamiltonian Monte Carlo to Get MCMC Sample Result

Description

This function uses Hamiltonian Monte Carlo (HMC) to generate samples for Markov Chain Monte Carlo (MCMC) sampling from a target distribution specified by neg_log_den_func. Each iteration performs a full HMC update to generate a new sample position.

Usage

get_hmc_mcmc_result(
  neg_log_den_func,
  neg_log_den_grad_func,
  coefs_0,
  iter = 5,
  hmc_scale = 0.01,
  hmc_steps = 5
)

Arguments

neg_log_den_func	A function that computes the negative log-density of the target distribution at a given position.
neg_log_den_grad_func	A function that computes the gradient of neg_log_den_func at a given position.
coefs_0	A numeric vector specifying the initial position of the chain in the parameter space.
iter	An integer specifying the number of HMC sampling iterations. Defaults to 5.
hmc_scale	A numeric value representing the scale factor for the leapfrog step size in the HMC update. Defaults to 0.01.
hmc_steps	An integer specifying the number of leapfrog steps in each HMC update. Defaults to 5.

Value

A numeric vector representing the final position in the parameter space after the specified number of iterations.

catalytic documentation built on April 4, 2025, 5:51 a.m.