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highD2pop (version 1.0)

Two-Sample Tests for Equality of Means in High Dimension

Description

Performs the generalized component test from Gregory et al (2015), as well as the tests from Chen and Qin (2010), Srivastava and Kubokawa (2013), and Cai, Liu, and Xia (2014) for equality of two population mean vectors when the length of the vectors exceeds the sample size.

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Version

Install

install.packages('highD2pop')

Monthly Downloads

5

Version

1.0

License

GPL (>= 2)

Maintainer

Karl Gregory

Last Published

October 24th, 2014

Functions in highD2pop (1.0)

Chen Qin Simulator

Srivastava and Kubokawa test for equal means

CLX.test.equalcov

Cai, Liu, and Xia equal means test under equal covariances

Generalized component test simulator

Generalized component test

CLX.sim.unequalcov

Cai, Liu, and Xia equal means test simulator under unequal covariances

Data simulator for the high-dimensional two-sample setting

The centered gamma distribution

build2popData_muYafunction

Data simulator for the high-dimensional two-sample setting

CLX.test.unequalcov

Cai, Liu, and Xia equal means test under unequal covariances

highD2pop-package

Two-sample tests for equality of means in high dimension

Srivastava and Kubokawa Simulator

CLX.sim.equalcov

Cai, Liu, and Xia equal means test simulator under equal covariances

Cai, Liu, and Xia test for equality of two mean vectors

The centering value for the test statistic

CLX.sim.Covtest

Cai, Liu, and Xia equal means test simulator

Copy number data along a segment of the q arm of chromosome 1

Chen's and Qin's test for equality of two mean vectors

The double pareto distribution

GCT.test.missing

Generalized component test for missing data