classSVD:

In musto101/wilcox_R: What the package does (short line)

Usage

classSVD(x)

Arguments

x

Examples

##---- Should be DIRECTLY executable !! ----
##-- ==>  Define data, use random,
##--	or do  help(data=index)  for the standard data sets.

## The function is currently defined as
function (x) 
{
    if (!is.matrix(x)) {
        stop("The function classSVD requires input of type 'matrix'.")
    }
    n <- nrow(x)
    p <- ncol(x)
    if (n == 1) {
        stop("The sample size is 1. No singular value decomposition can be performed.")
    }
    if (p < 5) {
        tolerance <- 1e-12
    }
    else {
        if (p <= 8) {
            tolerance <- 1e-14
        }
        else {
            tolerance <- 1e-16
        }
    }
    centerofX <- apply(x, 2, mean)
    Xcentered <- scale(x, center = TRUE, scale = FALSE)
    XcenteredSVD <- svd(Xcentered/sqrt(n - 1))
    rank <- sum(XcenteredSVD$d > tolerance)
    eigenvalues <- (XcenteredSVD$d[1:rank])^2
    loadings <- XcenteredSVD$v[, 1:rank]
    scores <- Xcentered %*% loadings
    return(list(loadings = as.matrix(loadings), scores = as.matrix(scores), 
        eigenvalues = as.vector(eigenvalues), rank = rank, Xcentered = as.matrix(Xcentered), 
        centerofX = as.vector(centerofX)))
  }

musto101/wilcox_R documentation built on May 23, 2019, 10:52 a.m.