MHAlogrithmmulti: Metropolis-Hastings Algorithm to sample data from...

In wzh96/STAT600RPackage: Implementing Metropolis-Hastings Algorithm

Description

Metropolis-Hastings Algorithm to sample data from multivariate distribution

Usage

MHAlogrithmmulti(
  TargetDensity,
  nvar,
  CGDensity = "multivariateNormal",
  xinit = NULL,
  sigma = NULL,
  niter = 1000
)

Arguments

TargetDensity	A function: The PDF of target density function from which the users want to sample. This should be as a function of x.
nvar	A scalar: The number of variables
CGDensity	Candidate Generating Density function (default is multivariate normal distribution)
xinit	A vector: The starting point of the algorithm
sigma	A matrix: The covariance matrix of the candidate generating distribution
niter	A scalar: The number of data to sample

Value

Return the data collection sampled from the MH Algorithm

wzh96/STAT600RPackage documentation built on Dec. 23, 2021, 6:15 p.m.