ea_biGaussian_DL_PT: Diffusion probability for the Exact Algorithm for Langevin...

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

Diffusion probability for the Exact Algorithm for Langevin diffusion for bivariate tempered Gaussian distribution

Description

Simulate Langevin diffusion using the Exact Algorithm where pi = bivariate tempered Gaussian distribution

Usage

ea_biGaussian_DL_PT(
  x0,
  y,
  s,
  t,
  mean_vec,
  sd_vec,
  corr,
  beta,
  precondition_mat,
  transform_mats,
  diffusion_estimator = "Poisson",
  beta_NB = 10,
  gamma_NB_n_points = 2,
  logarithm
)

Arguments

x0	start value (vector of length 2)
y	end value (vector of length 2)
s	start time
t	end time
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
beta	real value
precondition_mat	precondition matrix
transform_mats	list of transformation matrices where transform_mats$to_Z is the transformation matrix to Z space and transform_mats$to_X is the transformation matrix to X space
diffusion_estimator	choice of unbiased estimator for the Exact Algorithm between "Poisson" (default) for Poisson estimator and "NB" for Negative Binomial estimator
beta_NB	beta parameter for Negative Binomial estimator (default 10)
gamma_NB_n_points	number of points used in the trapezoidal estimation of the integral found in the mean of the negative binomial estimator (default is 2)
logarithm	logical value to determine if log probability is returned (TRUE) or not (FALSE)

Value

acceptance probability of simulating Langevin diffusion with pi = bivariate tempered Gaussian distribution

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