bootstrip.limits:

In brentp/bootstrip: Resampling residuals of a linear model to determine significance.

Usage

bootstrip.limits(beta, probs = c(0.025, 0.975))

Arguments

beta
probs

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 (beta, probs = c(0.025, 0.975)) 
{
    pvalue = apply(beta, 1, function(row) {
        val = ecdf(row)(0)
        max(min(val, 1 - val) * 2, 1/length(row))
    })
    df = data.frame(pvalue)
    df$beta.mean = apply(beta, 1, mean)
    df$beta.median = apply(beta, 1, median)
    for (p in probs) {
        df[, paste0("beta.pct_", gsub(".", "p", p, fixed = T))] = apply(beta, 
            1, function(row) {
                quantile(row, probs = p)
            })
    }
    df
  }

brentp/bootstrip documentation built on May 13, 2019, 5:11 a.m.