testMean: Testing the equality of two sample mean vectors in high...

In HDtest: High Dimensional Hypothesis Testing for Mean Vectors, Covariance Matrices, and White Noise of Vector Time Series

Description

Testing the equality of two sample mean vectors in high dimension using different methods.

Usage

testMean(X, Y = NULL, method = "HD", m = 2500, filter = TRUE,
  alpha = 0.05, SX = NULL, SY = NULL)

Arguments

X	the n x p training data matrix, could be a matrix or a data.frame object.
Y	the n x p training data matrix, if presented the method will perform a two-sample test of mean, one-sample test otherwise. Could be a matrix or a data.frame object.
method	a string incidating the method for the test. The current available methods are ALL, HD, CQ, CLX.
m	the number of repetition in the test
filter	a logical indicator of the filtering process
alpha	the significant level of the test.
SX	covariance matrix of X, if not presented it will be estimated from the input sample.
SY	covariance matrix of T, if not presented it will be estimated from the input sample.

Value

For method HD, the function returns two htest objects for non-studentized and studentized test respectively.

For method CLX and CQ, the function returns an htest object.

For method ALL: A list of four htest objects.

HD refers to arXiv:1406.1939 [math.ST]

Author(s)

Tong He

Examples

data(GO54)
testMean(GO54$X, m = 100, method = "HD")
testMean(GO54$X, GO54$Y, m = 100, method = "ALL")

HDtest documentation built on May 2, 2019, 11:53 a.m.