\HeaderA{ldaCMA}{Linear Discriminant Analysis}{ldaCMA}
\keyword{multivariate}{ldaCMA}
\begin{Description}\relax
Performs a linear discriminant analysis under the assumption
of a multivariate normal distribution in each classes (with equal, but
generally structured) covariance matrices. The function \code{lda} from
the package \code{MASS} is called for computation.

For \code{S4} method information, see \LinkA{ldaCMA-methods}{ldaCMA.Rdash.methods}.
\end{Description}
\begin{Usage}
\begin{verbatim}
ldaCMA(X, y, f, learnind, ...)
\end{verbatim}
\end{Usage}
\begin{Arguments}
\begin{ldescription}
\item[\code{X}] Gene expression data. Can be one of the following:
\Itemize{
\item A \code{matrix}. Rows correspond to observations, columns to variables.
\item A \code{data.frame}, when \code{f} is \emph{not} missing (s. below).
\item An object of class \code{ExpressionSet}.
}

\item[\code{y}] Class labels. Can be one of the following:
\Itemize{
\item A \code{numeric} vector.
\item A \code{factor}.
\item A \code{character} if \code{X} is an \code{ExpressionSet} that
specifies the phenotype variable.
\item \code{missing}, if \code{X} is a \code{data.frame} and a
proper formula \code{f} is provided.
}
\bold{WARNING}: The class labels will be re-coded to
range from \code{0} to \code{K-1}, where \code{K} is the
total number of different classes in the learning set.

\item[\code{f}] A two-sided formula, if \code{X} is a \code{data.frame}. The
left part correspond to class labels, the right to variables.
\item[\code{learnind}] An index vector specifying the observations that
belong to the learning set. May be \code{missing};
in that case, the learning set consists of all
observations and predictions are made on the
learning set.
\item[\code{...}] Further arguments to be passed to \code{lda} from the
package \code{MASS}
\end{ldescription}
\end{Arguments}
\begin{Value}
An object of class \code{\LinkA{cloutput}{cloutput}}.
\end{Value}
\begin{Note}\relax
Excessive variable selection has usually to performed before
\code{ldaCMA} can be applied in the \code{p > n} setting.
Not reducing the number of variables can result in an error
message.
\end{Note}
\begin{Author}\relax
Martin Slawski \email{martin.slawski@campus.lmu.de}

Anne-Laure Boulesteix \url{http://www.slcmsr.net/boulesteix}
\end{Author}
\begin{References}\relax
McLachlan, G.J. (1992).

Discriminant Analysis and Statistical Pattern Recognition.

\emph{Wiley, New York}
\end{References}
\begin{SeeAlso}\relax
\code{\LinkA{compBoostCMA}{compBoostCMA}}, \code{\LinkA{dldaCMA}{dldaCMA}}, \code{\LinkA{ElasticNetCMA}{ElasticNetCMA}},
\code{\LinkA{fdaCMA}{fdaCMA}}, \code{\LinkA{flexdaCMA}{flexdaCMA}}, \code{\LinkA{gbmCMA}{gbmCMA}},
\code{\LinkA{knnCMA}{knnCMA}}, \code{\LinkA{LassoCMA}{LassoCMA}}, \code{\LinkA{nnetCMA}{nnetCMA}},
\code{\LinkA{pknnCMA}{pknnCMA}}, \code{\LinkA{plrCMA}{plrCMA}}, \code{\LinkA{pls\_ldaCMA}{pls.Rul.ldaCMA}},
\code{\LinkA{pls\_lrCMA}{pls.Rul.lrCMA}}, \code{\LinkA{pls\_rfCMA}{pls.Rul.rfCMA}}, \code{\LinkA{pnnCMA}{pnnCMA}},
\code{\LinkA{qdaCMA}{qdaCMA}}, \code{\LinkA{rfCMA}{rfCMA}}, \code{\LinkA{scdaCMA}{scdaCMA}},
\code{\LinkA{shrinkldaCMA}{shrinkldaCMA}}, \code{\LinkA{svmCMA}{svmCMA}}
\end{SeeAlso}
\begin{Examples}
\begin{ExampleCode}
### load Golub AML/ALL data
data(golub)
### extract class labels
golubY <- golub[,1]
### extract gene expression from first 10 genes
golubX <- as.matrix(golub[,2:11])
### select learningset
ratio <- 2/3
set.seed(111)
learnind <- sample(length(golubY), size=floor(ratio*length(golubY)))
### run LDA
ldaresult <- ldaCMA(X=golubX, y=golubY, learnind=learnind)
### show results
show(ldaresult)
ftable(ldaresult)
plot(ldaresult)
### multiclass example:
### load Khan data
data(khan)
### extract class labels
khanY <- khan[,1]
### extract gene expression from first 10 genes
khanX <- as.matrix(khan[,2:11])
### select learningset
set.seed(111)
learnind <- sample(length(khanY), size=floor(ratio*length(khanY)))
### run LDA
ldaresult <- ldaCMA(X=khanX, y=khanY, learnind=learnind)
### show results
show(ldaresult)
ftable(ldaresult)
plot(ldaresult)
\end{ExampleCode}
\end{Examples}

