Either a vector of one or more elements from which to choose, or a positive integer.
prob
A vector of probability weights for obtaining the elements of the vector being sampled.
groups
a vector (or variable in a data frame) specifying
groups to sample within. This will be recycled if necessary.
orig.ids
a logical; should origianal ids be included in returned data frame?
size
a non-negative integer giving the number of items to choose.
fixed
a vector of column names. These variables are shuffled en masse,
preserving associations among these columns.
shuffled
a vector of column names.
these variables are reshuffled individually (within groups if groups is
specified), breaking associations among these columns.
examples.
invisibly.return
a logical, should return be invisible?
drop.unused.levels
a logical, should unused levels be dropped?
...
additional arguments passed to
sample
or sample.
Details
These functions are wrappers around sample providing different defaults and
natural names.
Examples
# 100 Bernoulli trials -- no need for replace=TRUE
resample(0:1, 100)
tally(resample(0:1, 100))
if (require(mosaicData)) {
Small <- sample(KidsFeet, 10)
resample(Small)
tally(~ sex, data=resample(Small))
tally(~ sex, data=resample(Small))
# fixed marginals for sex
tally(~ sex, data=Small)
tally(~ sex, data=resample(Small, groups=sex))
# shuffled can be used to reshuffle some variables within groups
# orig.id shows where the values were in original data frame.
Small <- mutate(Small,
id1 = paste(sex,1:10, sep=":"),
id2 = paste(sex,1:10, sep=":"))
resample(Small, groups=sex, shuffled=c("id1","id2"))
}
deal(Cards, 13) # A Bridge hand
shuffle(Cards)