Bootstrapping in R Is there anyway to perform a BCa, a tilted, and an ABC bootstrap in R without using the built in packages, namely 'boot'? Thanks
 A: I'm guessing that you want to know the details of how to implement these functions yourself. If so, you can simply look at the source code of the boot package, which is available from CRAN. For example, the BCa is calculated with the function:
bca.ci <-
    function(boot.out,conf = 0.95,index = 1,t0 = NULL,t = NULL, L = NULL,
             h = function(t) t, hdot = function(t) 1, hinv = function(t) t,
             ...)
#
#  Adjusted Percentile (BCa) Confidence interval method.  This method
#  uses quantities calculated from the empirical influence values to
#  improve on the precentile interval.  Usually the required order
#  statistics for this method will not be integers and so norm.inter
#  is used to find them.
#
{
    t.o <- t
    if (is.null(t) || is.null(t0)) {
        t <- boot.out$t[,index]
            t0 <- boot.out$t0[index]
    }
    t <- t[is.finite(t)]
    w <- qnorm(sum(t < t0)/length(t))
    if (!is.finite(w)) stop("estimated adjustment 'w' is infinite")
    alpha <- (1+c(-conf,conf))/2
    zalpha <- qnorm(alpha)
    if (is.null(L))
        L <- empinf(boot.out, index=index, t=t.o, ...)
    a <- sum(L^3)/(6*sum(L^2)^1.5)
    if (!is.finite(a)) stop("estimated adjustment 'a' is NA")
    adj.alpha <- pnorm(w + (w+zalpha)/(1-a*(w+zalpha)))
    qq <- norm.inter(t,adj.alpha)
    cbind(conf, matrix(qq[,1L],ncol=2L), matrix(hinv(h(qq[,2L])),ncol=2L))
}

Of course, it would be useful reading the papers that describe these methods.
