\name{dudi.rwcoa}
 \alias{dudi.rwcoa}
 \title{Row weighted Correspondence Analysis}
 \description{
 \code{dudi.rwcoa} Row weighted COA, calls \code{forrwcoa} to perform row
 weighted correspondence analysis.
 }
 \usage{
 dudi.rwcoa(df, rowweights = rep(1/nrow(df),nrow(df)), ...)
 
 }
 
 \arguments{
   \item{df}{a \code{data.frame} containing positive or null values. It should not
     contain missing (NA) values. }
   \item{rowweights}{ a vector of row weights (by default, uniform row weights) }
   \item{\dots}{further arguments passed to or from other methods ) }
 }
 \details{
 Performs row weighted COA. Calls \code{forrwcoa} to calculates weights.
 }
 \value{
 Returns a list of class 'coa', 'rwcoa', and 'dudi' (see \code{\link[ade4:dudi]{dudi}}) 
 }
 \references{ Culhane AC, et al., 2003 Cross platform comparison and visualisation of gene expression data using co-inertia analysis.  BMC Bioinformatics. 4:59  }
 \author{ Aedin Culhane,  A.B. Dufour }
 \note{ In the paper by Culhane et al., 2002, coinertia analysis
   was performed with two COAs, a standard \code{\link[ade4:dudi.coa]{COA}} and a row weighted COA \code{dudi.rwcoa}, on
   the two gene expression datasets. However it is now recommended to perform
   two non-symmetric COA, instead of two COA. This avoids having to force
 the row weights from one analysis on the second.  To perform
 non-symmetric correspondence coinertia analysis, use \code{\link[made4:bet.coinertia]{bet.coinertia}}.}
 
  \seealso{ See Also as
    \code{\link[ade4:dudi]{dudi}},\code{\link[ade4:dudi.coa]{dudi.coa}},\code{\link[ade4:dudi.pca]{dudi.pca}}}
 
 \keyword{internal}