rtmvt: Truncated Multivariate Student t Distribution

In suchitm/tmvn: Generate random samples from truncated univariate and multivariate normal distributions and truncated Student-t distributions.

Description

This function generates random vectors form the truncates multivariate Student t distribution. It uses random sampling from rtmvn since the Student t distribution can be represented as a scale-mixture of normals.

Usage

rtmvt(n, Mean, Sigma, nu, D, lower, upper, init)

Arguments

n	number of samples to be generated
Mean	mean vector
Sigma	covariance matrix
nu	degress of freedom for the t-distribution
D	matrix of linear constraints
lower	vector of lower bounds
upper	vector of upper bounds
init	vector of initial values for the Gibbs sampler. Must satisfy the linear constraints.

Value

a matrix of samples with each column being an idependent sample.

References

Li, Y., & Ghosh, S. K. (2015). Efficient sampling methods for truncated multivariate normal and student-t distributions subject to linear inequality constraints. Journal of Statistical Theory and Practice, 9(4), 712-732.

Examples

Mean = rep(0,2)
rho = 0.5
Sigma = matrix(c(10,rho,rho,0.1),2,2)
D = matrix(c(1,1,1,-1),2,2)
varp = Sigma[1,1]+Sigma[2,2]+2*Sigma[1,2] # var of the sum
varm = Sigma[1,1]+Sigma[2,2]-2*Sigma[1,2] # var of the diff
sd = c(sqrt(varp),sqrt(varm))
lower = -1.5*sd; upper = 1.5*sd; int = rep(0,2)
nu = 5
n = 20
rtmvt(n,Mean,Sigma,nu,D,lower,upper,int)

suchitm/tmvn documentation built on Dec. 10, 2020, 10:25 a.m.