\name{residualsEcdfPlot}
\Rdversion{1.1}
\alias{residualsEcdfPlot}
\title{
Produce a diagnostic plot to check the fit of a raw variance function.
}
\description{
The residuals of the fit should follow a scaled chi-squared distribution. This function
calls \code{\link{varianceFitDiagnostics}} to get the cumulative chi-squared 
probabilities of the residuals and plots their ECDFs, stratified by base means.
}
\usage{
residualsEcdfPlot(cds, condition, ncuts = 7)
}
\arguments{
  \item{cds}{
     a CountDataSet with raw variance functions     
}
  \item{condition}{
     the name of a condition
}
  \item{ncuts}{
     the number of base mean strata (i.e, of curves)
}
}
\details{
   As the cumulative chi-square probabilities should be uniform, the ECDF curves
   should roughly follow the main diagonal (indicated by a green line). It is
   acceptable if the strata for very low counts deviate from this.
}
\value{
None, but a plot is produced.
}
\seealso{
\code{\link{residualsEcdfPlotFromDiagnostics}}, \code{\link{varianceFitDiagnostics}}
}
\examples{
cds <- makeExampleCountDataSet()
cds <- estimateSizeFactors( cds )
cds <- estimateVarianceFunctions( cds )
residualsEcdfPlot( cds, "A" )
}