bootstrap | R Documentation |
Generate a vector of bootstrap samples.
bootstrap( x, trt = NULL, trt_control = "Control", FUN = NULL, varname = NULL, varcol = NULL, arglist = NULL, n_samples = 1 )
x |
Source data to bootstrap. |
trt |
Treatment variable. (optional) |
trt_control |
Value for treatment control arm. Default value is 'Control'. |
FUN |
Function to compute statistic for each bootstrap sample. (optional) |
varname |
Name of variable in x on which to compute FUN. If x has only one column varname is not needed. If x has more than one column then either varname or varcol must be specified. |
varcol |
Column index of x on which to compute FUN. If x has only one column varcol is not needed. If x has more than one column then either varname or varcol must be specified. |
arglist |
List of additional arguments to pass to FUN. |
n_samples |
Number of bootstrap samples to generate. |
Each bootstrap sample will retain the in-bag and out-of-bag data. Optionally, the user may specify a function to compute a statistic for each in-bag and out-of-bag sample. This function may be a built-in R function (e.g. mean, median, etc.) or a user-defined function (see Examples). If no statistic function is provided bootstrap returns a vector of objects of class Bootstrap. If a statistic function is provided bootstrap returns a vector of objects of class BootstrapStatistic, which in addition to the in-bag and out-of-bag samples contains the name of the statistic, variable on which the statistic is computed, and the numerical result of the statistic for each in-bag and out-of-bag sample.
If FUN is NULL returns a vector of objects of class Bootstrap. If FUN is non-NULL returns a vector of objects of class BootstrapStatistic
Bootstrap, BootstrapStatistic
## Generate example data frame containing response and treatment N <- 20 x <- data.frame( runif( N ) ) names( x ) <- "response" x$treatment <- factor( sample( c("Control","Experimental"), size = N, prob = c(0.8,0.2), replace = TRUE ) ) ## Generate two bootstrap samples without regard to treatment ex1 <- bootstrap( x, n_samples = 2 ) ## Generate two bootstrap samples stratified by treatment ex2 <- bootstrap( x, trt = x$treatment, trt_control = "Control", n_samples = 2 ) ## For each bootstrap sample compute a statistic on the in-bag and out-of-bag data ex3 <- bootstrap( x, FUN = mean, varname = "response", n_samples = 2 ) ## Specify a user-defined function that takes a numeric vector input and ## returns a numeric result sort_and_rank <- function( z, rank ){ z <- sort( z ) return( z[rank] ) } ex4 <- bootstrap( x, FUN = sort_and_rank, arglist = list( rank = 1 ), varname = "response", n_samples = 2 )
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