R/cvm.test.R

In nortest: Tests for Normality

"cvm.test" <-
function (x) 
{
    DNAME <- deparse(substitute(x))
    x <- sort(x[complete.cases(x)])
    n <- length(x)
    if (n < 8) 
        stop("sample size must be greater than 7")
    p <- pnorm((x - mean(x))/sd(x))
    W <- (1/(12 * n) + 
        sum(
            (p - (2 * seq(1:n) - 1)/(2 * n))^2
        ))
    WW <- (1 + 0.5/n) * W
    if (WW < 0.0275) {
        pval <- 1 - exp(-13.953 + 775.5 * WW - 12542.61 * WW^2)
    }
    else if (WW < 0.051) {
        pval <- 1 - exp(-5.903 + 179.546 * WW - 1515.29 * WW^2)
    }
    else if (WW < 0.092) {
        pval <- exp(0.886 - 31.62 * WW + 10.897 * WW^2)
    }
    else if (WW < 1.1) {
        pval <- exp(1.111 - 34.242 * WW + 12.832 * WW^2)
    }
    else {
        warning("p-value is smaller than 7.37e-10, cannot be computed more accurately")
        pval <- 7.37e-10
    }
    RVAL <- list(statistic = c(W = W), p.value = pval, method = "Cramer-von Mises normality test", 
        data.name = DNAME)
    class(RVAL) <- "htest"
    return(RVAL)
}