equalCovs: Testing the equality of two covariance matrices.

In equalCovs: Testing the Equality of Two Covariance Matrices

Description

R code for testing the equality of two covariance matrices, used in paper "Two sample tests for high dimensional covariance matrices".

Usage

equalCovs(sam1, sam2, size1, size2)

Arguments

sam1	First sample, it must be array with structure size1*p, p is the dimension of data.
sam2	Second sample, it must be array with structure size2*p, p is the dimension of data.
size1	sample size of first sample
size2	sample size of second sample

Value

test statistics and p-values

test_stat	test statistics
pvalue	p-values

Author(s)

Jun Li and Song Xi Chen

Examples

library(mvtnorm)
p<-700 # the dimension of multivariate

theta1<-2
theta2<-1
mat1<-diag(theta1,p-1)
mat2<-diag(theta1+theta1*theta2,p-1)
mat3<-diag(theta2,p-2)

mat1<-rbind(mat1,rep(0,p-1))
mat2<-rbind(mat2,rep(0,p-1))
mat3<-rbind(mat3,rep(0,p-2),rep(0,p-2))

mat1<-cbind(rep(0,p),mat1)
mat2<-cbind(rep(0,p),mat2)
mat3<-cbind(rep(0,p),rep(0,p),mat3)
sigma1<-mat1+t(mat1)+diag(1+theta1^2,p)
sigma2<-mat2+t(mat2)+mat3+t(mat3)+diag(1+theta1^2+theta2^2,p)

size1<-80
size2<-80
sam1<-rmvnorm(size1,runif(p,0,5),sigma1) # generate the samples
sam2<-rmvnorm(size2,runif(p,-3,3),sigma2)

equalCovs(sam1,sam2,size1,size2)

equalCovs documentation built on May 2, 2019, 12:40 p.m.