two.boot {simpleboot} | R Documentation |
two.boot
is used to bootstrap the difference between various
univariate statistics. An example is the difference of means.
Bootstrapping is
done by independently resampling from sample1
and sample2
.
two.boot(sample1, sample2, FUN, R, student = FALSE, M, weights = NULL, ...)
sample1 |
First sample; a vector of numbers. |
sample2 |
Second sample; a vector of numbers. |
FUN |
The statistic which is applied to each sample. This can be a quoted string or a function name. |
R |
Number of bootstrap replicates. |
student |
Should we do a studentized bootstrap? This requires a double bootstrap so it might take longer. |
M |
If student is set to TRUE , then M is the
number of internal bootstrap replications to do. |
weights |
Resampling weights; a list with two components. The
first component of the list is a vector of weights for
sample1 and the second component of the list is a vector of
weights for sample2 . |
... |
Other (named) arguments that should be passed to
FUN . |
The differences are always taken as FUN(sample1) -
FUN(sample2)
. If you want the difference to be reversed you need
to reverse the order of the arguments sample1
and
sample2
.
An object of class "simpleboot"
, which is almost identical to the
regular "boot"
object. For example, the boot.ci
function can be used on this object.
Roger D. Peng
set.seed(50) x <- rnorm(100, 1) ## Mean 1 normals y <- rnorm(100, 0) ## Mean 0 normals b <- two.boot(x, y, median, R = 1000) boot.ci(b) ## No studentized confidence intervals hist(b) ## Histogram of the bootstrap replicates b <- two.boot(x, y, quantile, R = 1000, probs = .75) ## With weighting ## Here all members of the first group has equal weighting ## but members of the the second have unequal weighting w <- list(rep(1, 100), 100:1) bw <- two.boot(x, y, median, R = 1000, weights = w) boot.ci(b) ## Studentized bstud <- two.boot(x, y, median, R = 500, student = TRUE, M = 50) boot.ci(bstud, type = "stud") ## Studentized with weights bwstud <- two.boot(x, y, median, R = 500, student = TRUE, M = 50, weights = w) boot.ci(bstud, type = "stud")