intern.sam {globalSeq} | R Documentation |
These functions calculate the contribution of covariate
or samples to the test statistic.
They are called by the function proprius
.
intern.sam(y, X, mu, phi) intern.cov(y, X, mu, phi)
y |
response variable: numeric vector of length |
X |
covariate set: numeric matrix with |
mu |
mean parameters: numeric vector of length |
phi |
dispersion parameter: non-negative real number |
Both functions return a numeric vector.
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)
This is an internal
function. The user functions
of the R package globalSeq
are cursus
,
omnibus
, and proprius
.
# 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)