fusion_multiGaussian: Generalised Monte Carlo Fusion (rejection sampling) [on a...

In rchan26/hierarchicalFusion: Divide-and-Conquer Monte Carlo Fusion

Generalised Monte Carlo Fusion (rejection sampling) [on a single core]

Description

Generalised Monte Carlo Fusion with multivariate Gaussian target

Usage

fusion_multiGaussian(
  N,
  m,
  time,
  samples_to_fuse,
  dim,
  mu,
  inv_Sigma,
  betas,
  precondition_matrices,
  inv_precondition_matrices
)

Arguments

N	number of samples
m	number of sub-posteriors to combine
time	time T for fusion algorithm
samples_to_fuse	list of length m, where samples_to_fuse[c] containing the samples for the c-th sub-posterior
dim	dimension
mu	vector of length dim for mean
inv_Sigma	dim x dim inverse covariance matrix
betas	vector of length m, where betas[c] is the inverse temperature (beta) for c-th sub-posterior (can also pass in one number if they are all at the same inverse temperature)
precondition_matrices	list of length m, where precondition_matrices[[c]] is the precondition matrix for sub-posterior c

Value

samples: fusion samples

iters_rho: number of iterations from the first accept/reject step (rho)

iters_Q: number of iterations from the second (diffusion) accept/reject step (Q)

rchan26/hierarchicalFusion documentation built on Sept. 11, 2022, 10:30 p.m.