progressive_fusion_biGaussian: (Progressive) D&C Monte Carlo Fusion (rejection sampling)

View source: R/bivariate_Gaussian_fusion.R

progressive_fusion_biGaussianR Documentation

(Progressive) D&C Monte Carlo Fusion (rejection sampling)

Description

(Progressive) D&C Monte Carlo Fusion with bivariate Gaussian target

Usage

progressive_fusion_biGaussian(
  N_schedule,
  time_schedule,
  mean_vec,
  sd_vec,
  corr,
  start_beta,
  base_samples,
  precondition = TRUE,
  seed = NULL,
  n_cores = parallel::detectCores()
)

Arguments

N_schedule

vector of length (L-1), where N_schedule[l] is the number of samples per node at level l

time_schedule

vector of length(L-1), where time_schedule[l] is the time chosen for Fusion at level l

mean_vec

vector of length 2 for mean

sd_vec

vector of length 2 for standard deviation

corr

correlation value between component 1 and component 2

start_beta

beta for the base level

base_samples

list of length (1/start_beta), where base_samples[[c]] contains the samples for the c-th node in the level

precondition

either a logical value to determine if preconditioning matrices are used (TRUE - and is set to be the variance of the sub-posterior samples) or not (FALSE - and is set to be the identity matrix for all sub-posteriors), or a list of length (1/start_beta) where precondition[[c]] is the preconditioning matrix for sub-posterior c. Default is TRUE

seed

seed number - default is NULL, meaning there is no seed

n_cores

number of cores to use

Value

A list with components:

samples

list of length (L-1), where samples[[l]][[i]] are the samples for level l, node i

time

list of length (L-1), where time[[l]][[i]] is the run time for level l, node i

rho_acc

list of length (L-1), where rho_acc[[l]][i] is the acceptance rate for first fusion step for level l, node i

Q_acc

list of length (L-1), where Q_acc[[l]][i] is the acceptance rate for second fusion step for level l, node i

rhoQ_acc

list of length (L-1), where rhoQ_acc[[l]][i] is the overall acceptance rate for fusion for level l, node i

diffusion_times

vector of length (L-1), where diffusion_times[l] are the times for fusion in level l (= time_schedule)

precondition_matrices

preconditioning matrices used in the algorithm for each node


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