lsfitNci:

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

Usage

lsfitNci(x, y, alpha = 0.05)

Arguments

x
y
alpha

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, y, alpha = 0.05) 
{
    x <- as.matrix(x)
    if (nrow(x) != length(y)) 
        stop("Length of y does not match number of x values")
    m <- cbind(x, y)
    m <- elimna(m)
    y <- m[, ncol(x) + 1]
    temp <- lsfit(x, y)
    x <- cbind(rep(1, nrow(x)), m[, 1:ncol(x)])
    xtx <- solve(t(x) %*% x)
    h <- diag(x %*% xtx %*% t(x))
    hc3 <- xtx %*% t(x) %*% diag(temp$res^2/(1 - h)^2) %*% x %*% 
        xtx
    df <- nrow(x) - ncol(x)
    crit <- qt(1 - alpha/2, df)
    al <- ncol(x)
    ci <- matrix(NA, nrow = al, ncol = 3)
    for (j in 1:al) {
        ci[j, 1] <- j
        ci[j, 2] <- temp$coef[j] - crit * sqrt(hc3[j, j])
        ci[j, 3] <- temp$coef[j] + crit * sqrt(hc3[j, j])
    }
    print("Confidence intervals for intercept followed by slopes:")
    list(ci = ci, stand.errors = sqrt(diag(hc3)))
  }

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