GCT.sim: Generalized component test simulator

In highD2pop: Two-Sample Tests for Equality of Means in High Dimension

Description

Performs the generalized component test from Gregory et al. (2014) on multiple data sets generated by build2popData.

Usage

GCT.sim(DATA, r, smoother = "parzen", ntoorderminus = 2)

Arguments

DATA	an object returned by build2popData which is a list of S data sets.
r	the lag window size for variance estimation.
smoother	the lag window used in the variance estimation. Possible values are "parzen" and "trapezoid".
ntoorderminus	a value of 0,1, or 2 such that the centering constant will retain terms of order n^(-ntoorderminus). Enter 0 for the moderate-p GCT, and enter 2 for the large-p GCT. A value of 1 may be entered to retain only terms which are O(1/n), appropriate for a size of p between moderate and large.

Value

A data frame with columns

TSvalues	the values of the unstudentized test statistic.
pvalues	the p-values.
smoothtype	the choice of the lag window used in variance estimation.
T	the values of the studentized test statistic.
cent	the values of the centering constant.
var	the values of the estimated variance of the test statistic.

Author(s)

Karl Gregory [e-mail], http://www.stat.tamu.edu/~kbgregory.

References

Gregory, K., Carroll, R. J., Baladandayuthapani, V. and Lahiri, S. (2015). A two-sample test for equality of means in high dimension. Journal of the American Statistician, to appear

See Also

GCT.test

Examples

	
## Not run: 

DATA <-build2popData(	
	n = 15,
	m = 20,
	p = 500,
	muX = rep(0,500),
	muY = rep(0,500),
	commoncov = FALSE,
	VarScaleY = 1,
	dep = "ARMA",
	ARMAparms = list(coefs=list(ma=c(.2,.3) , ar=c(.4,-.1))),
	LRparm = .75,
	S = 25,
	innov = function(n,...) rnorm(n,0,1),
	heteroscedastic=TRUE,
	het.diag = diag(.1 + rexp(500,1/2))
	)	
	
GCT.sim(DATA,r=20,smoother="parzen")


## End(Not run)

highD2pop documentation built on May 2, 2019, 5:11 a.m.