R/orthonorm.R

In ldr: Methods for likelihood-based dimension reduction in regression

orthonorm <-
function(u) 
	{
		if (is.null(u)) return(NULL)
		if (!(is.matrix(u))) u <- as.matrix(u);
		dd <- dim(u); n <- dd[1]; p <-dd[2];

		if (prod(abs(La.svd(u)$d) > 1e-08) == 0) stop("collinears vectors in orthonorm")
		if (n < p)
		{
			warning("There are too many vectors to orthonormalize in orthonorm.")
			u <- as.matrix(u[, 1:p])
			n <- p
    		}
    		v <- u;
    		if (p > 1)
		{
			for (i in 2:p)
			{
				coef.proj <- c(crossprod(u[, i], v[, 1:(i - 1)]))/diag(crossprod(v[, 1:(i - 1)]));
				v[, i] <- u[, i] - matrix(v[, 1:(i - 1)], nrow = n) %*% matrix(coef.proj, nrow = i - 1)
			}
    		}
		coef.proj <- 1/sqrt(diag(crossprod(v)))
		return(t(t(v) * coef.proj))
	}