\name{nem.bootstrap}
\alias{nem.bootstrap}
\alias{print.nem.bootstrap}

\title{Bootstrapping for nested effect models}
\description{Performs bootstrapping (resampling with replacement) on effect reporters to assess the statistical stability of networks}
\usage{
nem.bootstrap(D, thresh=0.5, nboot=1000,inference="nem.greedy",models=NULL,control=set.default.parameters(unique(colnames(D))), verbose=TRUE)

\method{print}{nem.bootstrap}(x, ...)
}

\arguments{  
  \item{D}{data matrix with experiments in the columns (binary or continous)}
  \item{thresh}{only edges appearing with a higher frequency than "thresh" are returned}
  \item{nboot}{number of bootstrap samples desired}
  \item{inference}{\code{search} to use exhaustive enumeration, \code{triples} for triple-based inference, \code{pairwise} for the pairwise heuristic, \code{ModuleNetwork} for the module based inference, \code{nem.greedy} for greedy hillclimbing, \code{nem.greedyMAP} for alternating MAP optimization using log odds or log p-value densities}
  \item{models}{a list of adjacency matrices for model search. If NULL, an  exhaustive enumeration of all possible models is performed.}
  \item{control}{list of parameters: see \code{set.default.parameters}}
  \item{verbose}{do you want to see progression statements? Default: TRUE}

  \item{x}{nem object}
  \item{...}{other arguments to pass}
}
\details{
  Calls \code{\link{nem}} or \code{\link{nemModelSelection}} internally, depending on whether or not lambda is a vector and Pm != NULL. For DEPNs a stratified bootstrap is carried out, where strate are defined on each replicate group for each time point.
}
\value{
	nem object with edge weights being the bootstrap probabilities
}

\author{Holger Froehlich}


\seealso{\code{\link{nem.jackknife}}, \code{\link{nem.consensus}}, \code{\link{nem.calcSignificance}}, \code{\link{nem}}}
\examples{
\dontrun{
   data("BoutrosRNAi2002")
   D <- BoutrosRNAiDiscrete[,9:16]
   nem.bootstrap(D, control=set.default.parameters(unique(colnames(D)), para=c(0.13,0.05)))         
}
}
\keyword{graphs}
\keyword{models}