Nothing
# Loosely based on vegan:::predict.decorana
# an example of stuff I don't need from
# vegan:::predict.decorana
# u <- sweep(x = oldDCA$rproj[ , 1, drop = FALSE],
# MARGIN = 2,
# STATS = oldDCA$origin[1],
# FUN = "-")
#
# v <- sweep(x = oldDCA$cproj[ , 1, drop = FALSE],
# MARGIN = 2,
# STATS = oldDCA$origin[1],
# FUN = "-")
# rs <- oldDCA$aidot/sum(oldDCA$aidot)
# u <- oldDCA$rproj[ , 1] - oldDCA$origin[1]
predictDCA_sites_dca1 <- function (
oldDCA,
newSample
){
cs <- oldDCA$adotj/sum(oldDCA$aidot)
v <- oldDCA$cproj[ , 1] - oldDCA$origin[1]
v <- v * sqrt(cs)
#
proj <- as.matrix(newSample)
if (!is.null(oldDCA$v)){
proj <- sweep(proj, 2, oldDCA$v, "*")
}
rs <- rowSums(proj)
proj <- (proj - outer(rs, cs))/sqrt(outer(rs, cs))
out <- sweep(proj %*% v, 1, sqrt(rs), "/")
return(out)
}
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