\HeaderA{impute.HMM}{Imputing log2 ratios using HMM}{impute.HMM}
\keyword{models}{impute.HMM}
\begin{Description}\relax
Imputing log2 ratios using the output of the HMM segmenttation
\end{Description}
\begin{Usage}
\begin{verbatim}
impute.HMM(aCGH.obj, chrominfo = human.chrom.info.Jul03, maxChrom =
23, use.BIC = TRUE)
\end{verbatim}
\end{Usage}
\begin{Arguments}
\begin{ldescription}
\item[\code{aCGH.obj}] Object of class aCGH.
\item[\code{chrominfo}] a chromosomal information associated with the mapping of the data
\item[\code{maxChrom}] Highest chromosome to impute.
\item[\code{use.BIC}] logical parameter; if true impute missing values based
on the Hidden Markov Model selected using Bayesian Information
Criterion impute missing data, otherwise use AIC.
\end{ldescription}
\end{Arguments}
\begin{Details}\relax
See details in \code{\LinkA{aCGH}{aCGH}} discussion.
\end{Details}
\begin{Value}
Computes and returns the imputed log2 ratio matrix of the aCGH object
using the output of the Hidden Markov Model segmentation done by
invoking \code{\LinkA{find.hmm.states}{find.hmm.states}} function.
\end{Value}
\begin{SeeAlso}\relax
\code{\LinkA{aCGH}{aCGH}}, \code{\LinkA{find.hmm.states}{find.hmm.states}}, \code{\LinkA{impute.lowess}{impute.lowess}}.
\end{SeeAlso}
\begin{Examples}
\begin{ExampleCode}

datadir <- system.file(package = "aCGH")
datadir <- paste(datadir, "/examples", sep="")

clones.info <-
      read.table(file = file.path(datadir, "clones.info.ex.txt"),
                 header = TRUE, sep = "\t", quote="", comment.char="")
log2.ratios <-
      read.table(file = file.path(datadir, "log2.ratios.ex.txt"),
                 header = TRUE, sep = "\t", quote="", comment.char="")
ex.acgh <- create.aCGH(log2.ratios, clones.info)

## Imputing the log2 ratios 

hmm(ex.acgh) <- find.hmm.states(ex.acgh, aic = TRUE, delta = 1.5)
log2.ratios.imputed(ex.acgh) <- impute.HMM(ex.acgh)

\end{ExampleCode}
\end{Examples}

