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"forrwcoa" <-
function(df, rowweights = rep(1/nrow(df),nrow(df))) {
# For row weighted correspondence analysis
# where df is a data frame rowweights a weighting row vector (by default the uniform weighting)
# The function returns a data frame which COA computes the required weighting.
# Use 'dudi.coa' on this result. Written by D. Chessel & A.B. Dufour June 2003 for A. Culhane
# example
# data(atlas)
# coa1=dudi.coa(atlas$birds,scannf=F)
# coa2=dudi.coa(forrwcoa(atlas$birds),scannf=F)
if (!is.data.frame(df))
stop("data.frame expected")
if (any(rowweights <0)) stop ("negative entries in row weighting")
if (length(rowweights)!= nrow(df)) stop ("non convenient length for 'rowweights'")
lig <- nrow(df)
col <- ncol(df)
if (any(df < 0))
stop("negative entries in table")
if ((N <- sum(df)) == 0)
stop("all frequencies are zero")
df <- df/N
row.w <- apply(df, 1, sum)
df <- df/row.w
df <- df*rowweights
return(df)
}
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