Classification functions in linear discriminant analysis in R

Question

After completing a linear discriminant analysis in R using lda(), is there a convenient way to extract the classification functions for each group?

Fro

Answer 1

There isn't a built-in way to get the information I needed, so I wrote a function to do it:

ty.lda <- function(x, groups){
  x.lda <- lda(groups ~ ., as.data.frame(x))

  gr <- length(unique(groups))   ## groups might be factors or numeric
  v <- ncol(x) ## variables
  m <- x.lda$means ## group means

  w <- array(NA, dim = c(v, v, gr))

  for(i in 1:gr){
    tmp <- scale(subset(x, groups == unique(groups)[i]), scale = FALSE)
    w[,,i] <- t(tmp) %*% tmp
  }

  W <- w[,,1]
  for(i in 2:gr)
    W <- W + w[,,i]

  V <- W/(nrow(x) - gr)
  iV <- solve(V)

  class.funs <- matrix(NA, nrow = v + 1, ncol = gr)
  colnames(class.funs) <- paste("group", 1:gr, sep=".")
  rownames(class.funs) <- c("constant", paste("var", 1:v, sep = "."))

  for(i in 1:gr) {
    class.funs[1, i] <- -0.5 * t(m[i,]) %*% iV %*% (m[i,])
    class.funs[2:(v+1) ,i] <- iV %*% (m[i,])
  }

  x.lda$class.funs <- class.funs

  return(x.lda)
}

This code follows the formulas in Legendre and Legendre's Numerical Ecology (1998), page 625, and matches the results of the worked example starting on page 626.