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\name{graph.T2.test}
\alias{graph.T2.test}

\title{Performs the Hotelling T2 test in Fourier space}

\description{
Performs the Hotelling T2 test in Fourier space.
}

\usage{graph.T2.test(X1, X2, G=NULL, lfA=NULL, ..., k=ncol(X1))}

\arguments{
\item{X1}{A n1 x p \code{\link[base]{numeric}} \code{\link[base]{matrix}}, observed data for class 1: p variables, n1
observations.}
\item{X2}{A n2 x p \code{\link[base]{numeric}} \code{\link[base]{matrix}}, observed data for class 2: p variables, n2
observations.}
\item{G}{An object of class \code{\link[=graphAM-class]{graphAM}} or
\code{\link[=graphNEL-class]{graphNEL}}, the graph to be used in the two-sample test.}
containing the Laplacian eigen vectors and eigen values}
\item{...}{Further arguments to be passed to \code{\link{laplacianFromA}}().}
\item{k}{A \code{\link[base]{numeric}} value, number of Fourier components retained for the
test.}
}

\value{
}

\author{Laurent Jacob, Pierre Neuvial and Sandrine Dudoit}

\seealso{
}

\examples{
library("rrcov")

## Some parameters
n1 <- n2 <- 20
nnodes <- nedges <- 20
k <- 3
ncp <- 0.5
sigma <- diag(nnodes)/sqrt(nnodes)

## Build graph, decompose laplacian
G <- randomWAMGraph(nnodes=nnodes,nedges=nedges)
U <- lfA$U l <- lfA$l
t <- T2.test(X$X1,X$X2) # Raw T-square
print(t$p.value) tu <- graph.T2.test(X$X1,X$X2,lfA=lfA,k=k) # Filtered T-squares print(tu$p.value)