\HeaderA{mt.sample.teststat}{Permutation distribution of test statistics and raw (unadjusted) p-values}{mt.sample.teststat}
\aliasA{mt.sample.label}{mt.sample.teststat}{mt.sample.label}
\aliasA{mt.sample.rawp}{mt.sample.teststat}{mt.sample.rawp}
\keyword{manip}{mt.sample.teststat}
\begin{Description}\relax
These functions provide tools to investigate the permutation distribution
of test statistics, raw (unadjusted) \eqn{p}{}-values, and class labels.
\end{Description}
\begin{Usage}
\begin{verbatim}
mt.sample.teststat(V,classlabel,test="t",fixed.seed.sampling="y",B=10000,na=.mt.naNUM,nonpara="n")
mt.sample.rawp(V,classlabel,test="t",side="abs",fixed.seed.sampling="y",B=10000,na=.mt.naNUM,nonpara="n")
mt.sample.label(classlabel,test="t",fixed.seed.sampling="y",B=10000)
\end{verbatim}
\end{Usage}
\begin{Arguments}
\begin{ldescription}
\item[\code{V}] A numeric vector containing the data for one of the variables (genes).
\item[\code{classlabel}] A vector of integers corresponding to observation (column)
class labels. For \eqn{k}{} classes, the labels must be integers
between 0 and \eqn{k-1}{}. For the \code{blockf} test option,
observations may be divided into
\eqn{n/k}{} blocks of \eqn{k}{} observations each. The observations are
ordered by block, and within each block, they are labeled using the
integers 0 to \eqn{k-1}{}.

\item[\code{test}] A character string specifying the statistic to be
used to test the null hypothesis of no association between the
variables and the class labels.\\
If \code{test="t"}, the tests are based on two-sample Welch t-statistics
(unequal variances).  \\
If \code{test="t.equalvar"}, the tests are based on two-sample
t-statistics with equal variance for the two samples. The
square of the t-statistic is equal to an F-statistic for \eqn{k=2}{}. \\
If \code{test="wilcoxon"}, the tests are based on standardized rank sum Wilcoxon statistics.\\
If \code{test="f"}, the tests are based on F-statistics.\\
If \code{test="pairt"}, the tests are based on paired t-statistics. The
square of the paired t-statistic is equal to a block F-statistic for \eqn{k=2}{}. \\
If \code{test="blockf"}, the tests are based on F-statistics which
adjust for block differences
(cf. two-way analysis of variance).

\item[\code{side}] A character string specifying the type of rejection region.\\
If \code{side="abs"}, two-tailed tests, the null hypothesis is rejected for large absolute values of the test statistic.\\
If \code{side="upper"}, one-tailed tests, the null hypothesis is rejected for large values of the test statistic.\\
If \code{side="lower"}, one-tailed tests,  the null hypothesis is rejected for small values of the test statistic.

\item[\code{fixed.seed.sampling}] If \code{fixed.seed.sampling="y"}, a
fixed seed sampling procedure is used, which may double the
computing time, but will not use extra memory to store the
permutations. If \code{fixed.seed.sampling="n"}, permutations will
be stored in memory.  For the \code{blockf} test, the option \code{n} was not implemented as it requires too much memory.

\item[\code{B}] The number of permutations. For a complete
enumeration, \code{B} should be 0 (zero) or any number not less than
the total number of permutations.

\item[\code{na}] Code for missing values (the default is \code{.mt.naNUM=--93074815.62}).
Entries with missing values will be ignored in the computation,
i.e., test statistics will be based on a smaller sample size. This
feature has not yet fully implemented.

\item[\code{nonpara}] If \code{nonpara}="y", nonparametric test statistics are computed based on ranked data. \\
If  \code{nonpara}="n", the original data are used.

\end{ldescription}
\end{Arguments}
\begin{Value}
For \code{\LinkA{mt.sample.teststat}{mt.sample.teststat}},  a vector containing \code{B} permutation test statistics. \\ \\
For \code{\LinkA{mt.sample.rawp}{mt.sample.rawp}},  a vector containing \code{B} permutation unadjusted \eqn{p}{}-values. \\\\ 
For \code{\LinkA{mt.sample.label}{mt.sample.label}}, a matrix containing \code{B}
sets of permuted class labels. Each row corresponds to one permutation.
\end{Value}
\begin{Author}\relax
Yongchao Ge, \email{yongchao.ge@mssm.edu}, \\
Sandrine Dudoit, \url{http://www.stat.berkeley.edu/~sandrine}.
\end{Author}
\begin{SeeAlso}\relax
\code{\LinkA{mt.maxT}{mt.maxT}}, \code{\LinkA{mt.minP}{mt.minP}}, \code{\LinkA{golub}{golub}}.
\end{SeeAlso}
\begin{Examples}
\begin{ExampleCode}

# Gene expression data from Golub et al. (1999)
data(golub)

mt.sample.label(golub.cl,B=10)

permt<-mt.sample.teststat(golub[1,],golub.cl,B=1000)
qqnorm(permt)
qqline(permt)

permt<-mt.sample.teststat(golub[50,],golub.cl,B=1000)
qqnorm(permt)
qqline(permt)

permp<-mt.sample.rawp(golub[1,],golub.cl,B=1000)
hist(permp)
\end{ExampleCode}
\end{Examples}