Greetings Jorge;
There certainly did not seem to be something readily apparent with
str(bmean), so the next logical place to look would be for a print
method. If you look at print.boot with:
getAywhere(print.boot)
... you see that the first portion sets up an internal structure
called "op" and the last of the function prints this with optional
headers. If you strip out the sections with headers you get:
lim.boot <- function (x, digits = getOption("digits"), index =
1L:ncol(boot.out$t),
...)
{
boot.out <- x
sim <- boot.out$sim
cl <- boot.out$call
t <- matrix(boot.out$t[, index], nrow = nrow(boot.out$t))
allNA <- apply(t, 2L, function(t) all(is.na(t)))
ind1 <- index[allNA]
index <- index[!allNA]
t <- matrix(t[, !allNA], nrow = nrow(t))
rn <- paste("t", index, "*", sep = "")
if (length(index) == 0L)
op <- NULL
else if (is.null(t0 <- boot.out$t0)) {
if (is.null(boot.out$call$weights))
op <- cbind(apply(t, 2L, mean, na.rm = TRUE), sqrt(apply(t,
2L, function(t.st) var(t.st[!is.na(t.st)]))))
else {
op <- NULL
for (i in index) op <- rbind(op, imp.moments(boot.out,
index = i)$rat)
op[, 2L] <- sqrt(op[, 2])
}
dimnames(op) <- list(rn, c("mean", "std. error"))
}
else {
t0 <- boot.out$t0[index]
if (is.null(boot.out$call$weights)) {
op <- cbind(t0, apply(t, 2L, mean, na.rm = TRUE) -
t0, sqrt(apply(t, 2L, function(t.st) var(t.st[!
is.na(t.st)]))))
dimnames(op) <- list(rn, c("original", " bias ",
" std. error"))
}
else {
op <- NULL
for (i in index) op <- rbind(op, imp.moments(boot.out,
index = i)$rat)
op <- cbind(t0, op[, 1L] - t0, sqrt(op[, 2L]), apply(t,
2L, mean, na.rm = TRUE))
dimnames(op) <- list(rn, c("original", " bias ",
" std. error", " mean(t*)"))
}
}
cat("\n\nBootstrap Statistics :\n")
if (!is.null(op))
print(op, digits = digits)
if (length(ind1) > 0L)
for (j in ind1) cat(paste("WARNING: All values of t",
j, "* are NA\n", sep = ""))
invisible(boot.out)
}
#--------------------------------
lim.boot(bmean)
Bootstrap Statistics :
original bias std. error
t1* 0.0904059 0.004641537 0.09239923
Probably too much in that function, but it does what was requested.
--
David Winsemius
On Mar 31, 2009, at 5:49 PM, Jorge Ivan Velez wrote:
Let's say I have the following:
# Loading the boot package
# install.packages(boot)
library(boot)
# Generating data
set.seed(123)
x <- rnorm(100)
# Bootstrap for the sample mean
bmean <- boot(x, function(x,d) mean(x[d]), R=1000)
bmean
#
#ORDINARY NONPARAMETRIC BOOTSTRAP
#
#
#Call:
#boot(data = x, statistic = function(x, d) mean(x[d]), R = 1000)
#
#
#Bootstrap Statistics :
# original bias std. error
#t1* 0.0904059 0.004641537 0.09239923
and I would like to get just this:
Bootstrap Statistics :
original bias std. error
t1* 0.0904059 0.004641537 0.09239923
How can I do that? I'm running R 2.8.1 Patched on XP SP2. Here is my
sessionInfo():
David Winsemius, MD
Heritage Laboratories
West Hartford, CT
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