meanmat.ts: Nonparametric Tests for the Mean Matrix

In HDTD: Statistical Inference about the Mean Matrix and the Covariance Matrices in High-Dimensional Transposable Data (HDTD)

Description

This function performs hypothesis testing for the mean matrix.

Usage

meanmat.ts(datamat, N, group.sizes, voi = "columns")

Arguments

datamat	numeric matrix containing the transposable data.
N	positive integer number indicating the sample size, i.e., the number of subjects.
group.sizes	numeric vector indicating the group sizes under the null hypothesis.
voi	character indicating if the test will be applied to the row or column variables. Options include 'rows' or 'columns'.

Details

It is assumed that there are nrow(datamat) row variables and ncol(datamat)/N column variables in datamat. Further, datamat should be written in such a way that every ncol(datamat)/N consecutive columns belong to the same subject and the order of the column variables in each block is preserved across subjects.

Value

Returns a list with components:

statistic	the value of the test statistic.
p.value	the corresponding p-value.
voi	the set of variables that the test was applied to.
n.groups	the number of groups under the null hypothesis.
group.sizes	the size of each group under the null hypothesis.
N	the sample size.
n.rows	the number of row variables.
n.cols	the number of column variables.

Author(s)

Anestis Touloumis

References

Touloumis, A., Tavare, S. and Marioni, J. C. (2015) Testing the Mean Matrix in High-Dimensional Transposable Data. Biometrics 71, 157–166.

Examples

data(VEGFmouse)
## Testing conservation of the overall gene expression across tissues.
tissues_mean_test <- meanmat.ts(datamat = VEGFmouse, N = 40, group.sizes = 9)
tissues_mean_test
## Testing if the adrenal and the cerebrum tissues have the same mean vector.
test2 <- meanmat.ts(VEGFmouse, N = 40, group.sizes = c(2, rep(1,7)))
test2

HDTD documentation built on Nov. 8, 2020, 8:25 p.m.