Simulates observations from a multinomial distribution.
Usage
resample(object, ...)
# S4 method for numeric
resample(object, do, n, size = sum(object), ..., f = NULL)
Arguments
- object
A
numeric
vector of count data (absolute frequencies).- ...
Extra arguments passed to
do
.- do
A
function
that takesobject
as an argument and returns a single numeric value.- n
A non-negative
integer
specifying the number of bootstrap replications.- size
A non-negative
integer
specifying the sample size.- f
A
function
that takes a single numeric vector (the result ofdo
) as argument.
Value
If f
is NULL
, resample()
returns the n
values of do
. Else,
returns the result of f
applied to the n
values of do
.
Examples
## Sample observations from a multinomial distribution
x <- sample(1:100, 50, TRUE)
resample(x, do = median, n = 100)
#> [1] 49.5 50.5 47.0 49.5 50.5 52.5 45.0 48.0 49.5 46.5 50.5 50.0 46.0 44.5 50.0
#> [16] 48.5 49.0 52.0 49.5 50.5 44.5 48.5 45.0 51.0 48.5 47.5 48.5 44.0 48.5 50.0
#> [31] 49.0 44.0 55.0 48.5 51.0 47.5 45.5 44.5 44.5 47.5 47.0 46.5 48.5 49.0 47.5
#> [46] 51.0 45.0 49.5 44.0 46.5 47.0 49.0 44.5 44.0 46.5 46.5 50.0 51.5 43.0 43.0
#> [61] 46.5 43.0 46.5 48.0 45.5 51.0 50.0 47.5 47.0 46.0 46.0 52.5 45.5 55.0 48.5
#> [76] 50.0 46.0 49.5 50.5 51.0 43.0 47.5 45.5 52.5 51.0 46.0 46.0 48.0 53.5 54.5
#> [91] 45.5 47.5 44.5 45.5 51.0 51.0 47.0 46.5 46.5 44.5
## Estimate the 25th, 50th and 95th percentiles
quant <- function(x) { quantile(x, probs = c(0.25, 0.50, 0.75)) }
resample(x, n = 100, do = median, f = quant)
#> 25% 50% 75%
#> 46.000 47.500 49.125