intern.sam: Internal function

In rauschenberger/globalSeq: Global Test for Counts

Description

These functions calculate the contribution of covariate or samples to the test statistic. They are called by the function proprius.

Usage

intern.sam(y, X, mu, phi)

intern.cov(y, X, mu, phi)

Arguments

y	response variable: numeric vector of length n
X	covariate set: numeric matrix with n rows (samples) and p columns (covariates)
mu	mean parameters: numeric vector of length n
phi	dispersion parameter: non-negative real number

Value

Both functions return a numeric vector.

References

A Rauschenberger, MA Jonker, MA van de Wiel, and RX Menezes (2016). "Testing for association between RNA-Seq and high-dimensional data", BMC Bioinformatics. 17:118. html pdf (open access)

JJ Goeman, SA van de Geer, F de Kort, and HC van Houwelingen (2004). "A global test for groups of genes: testing association with a clinical outcome", Bioinformatics. 20:93-99. html pdf (open access)

See Also

This is an internal function. The user functions of the R package globalSeq are cursus, omnibus, and proprius.

Examples

# simulate high-dimensional data
n <- 30
p <- 100
set.seed(1)
y <- rnbinom(n,mu=10,size=1/0.25)
X <- matrix(rnorm(n*p),nrow=n,ncol=p)

# prepare arguments
mu <- rep(mean(y),n)
phi <- (var(y)-mean(y))/mean(y)^2 

# decompose test statistic
intern.sam(y,X,mu,phi)
intern.cov(y,X,mu,phi)

rauschenberger/globalSeq documentation built on May 19, 2020, 4:09 a.m.