ea_exp_4_DL: Exact Algorithm for Langevin diffusion with pi =...

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

Exact Algorithm for Langevin diffusion with pi = exp(-(beta*(x-mean)^4)/2)

Description

Exact Algorithm with pi = exp(-(beta*(x-mean)^4)/2)

Usage

ea_exp_4_DL(
  N,
  input_samples,
  time,
  mean,
  beta,
  precondition,
  diffusion_estimator = "Poisson",
  beta_NB = 10,
  gamma_NB_n_points = 2
)

Arguments

N	number of samples
input_samples	input samples for the algorithm distributed according to pi = exp(-(beta*(x-mean)^4)/2)
time	time T for Exact Algorithm
mean	mean value
beta	real value
precondition	precondition value (i.e the covariance for the Langevin diffusion)
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)

Value

end points of the Exact Algorithm which should also be distributed according to pi = exp(-(beta*(x-mean)^4)/2)

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