bootstrap

From resample v0.4 by Tim Hesterberg

One and two sample bootstrap sampling and permutation tests.

Basic resampling. Supply the data and statistic to resample.

Keywords: htest, nonparametric

Usage

bootstrap(data, statistic, R = 10000,
          args.stat = NULL, seed = NULL, sampler = samp.bootstrap,
          label = NULL, statisticNames = NULL, block.size = 100,
          trace = FALSE)
bootstrap2(data, statistic, treatment, data2 = NULL, R = 10000,
          ratio = FALSE,
          args.stat = NULL, seed = NULL, sampler = samp.bootstrap,
          label = NULL, statisticNames = NULL, block.size = 100,
          trace = FALSE)
permutationTest(data, statistic, R = 9999,
          alternative = "two.sided", resampleColumns = NULL,
          args.stat = NULL, seed = NULL, sampler = samp.permute,
          label = NULL, statisticNames = NULL, block.size = 100,
          trace = FALSE, tolerance = .Machine$double.eps ^ 0.5)
permutationTest2(data, statistic, treatment, data2 = NULL, R = 9999,
          alternative = "two.sided", ratio = FALSE, paired = FALSE,
          args.stat = NULL, seed = NULL, sampler = samp.permute,
          label = NULL, statisticNames = NULL, block.size = 100,
          trace = FALSE, tolerance = .Machine$double.eps ^ 0.5)

Arguments

data: vector, matrix, or data frame.
statistic: a function, or expression (e.g. mean(myData, trim = .2).
R: number of replicates (bootstrap samples or permutation resamples).
treatment: a vector with two unique values. For two-sample applications, suppy either treatment or data2.
data2: an object like data; the second sample.
alternative: one of "two.sided", "greater", or "less". If statistic returns a vector, this may be a vector of the same length.
ratio: logical, if FALSE then statistics for two samples are combined using statistic1 - statistic2 (the statistics from the two samples). If TRUE, it uses statistic1 / statistic2.
resampleColumns: integer, or character (a subset of the column names of data); if supplied then only these columns of the data are permuted. For example, for a permutation test of the correlation of x and y, only one of the variables should be per
args.stat: a list of additional arguments to pass to statistic, if it is a function.
paired: logical, if TRUE then observations in data and data2 are paired, and permutations are done within each pair. Not yet implemented.
seed: old value of .Random.seed, or argument to set.seed.
sampler: a function for resampling, see help(samp.bootstrap).
label: used for labeling plots (in a future version).
statisticNames: a character vector the same length as the vector returned by statistic.
block.size: integer. The R replicates are done this many at a time.
trace: logical, if TRUE an indication of progress is printed.
tolerance: when computing P-values, differences smaller than tolerance (absolute or relative) between the observed value and the replicates are considered equal.

Details

There is considerable flexibility in how you specify the data and statistic.

For the statistic, you may supply a function, or an expression. For example, if data = x, you may specify any of

statistic = mean

statistic = mean(x) statistic = mean(data)

Value

a list with class "bootstrap", "bootstrap2", "permutationTest", or "permutationTest2", that inherits from "resample", with components:
observedthe value of the statistic for the original data.
replicatesa matrix with R rows and p columns.
nnumber of observations in the original data, or vector of length 2 in two-sample problems.
plength(observed).
Rnumber of replications.
seedthe value of the seed at the start of sampling.
callthe matched call.
statisticsa data frame with p rows, with columns "observed", "mean" (the mean of the replicates), and other columns appropriate to resampling; e.g. the bootstrap objects have columns "SE" and "Bias", while the permutation test objects have "Alternative" and "PValue".
The two-sample versions have an additional component:
resultsBothcontaining resampling results from each data set. containing two components, the results from resampling each of the two samples. These are bootstrap objects; in the permutationTest2 case they are the result of sampling without replacement.
There are functions for printing and plotting these objects, in particular print, hist, qqnorm, plot (currently the same as hist), quantile.

code

data2

itemize

statistic = colMeans(data)

item

statistic = mean(myData$x)
statistic = mean(myData[, "x"])

Examples

# See full set of examples in resample-package, including different
# ways to call the functions depending on the structure of the data.
data(Verizon)
CLEC <- with(Verizon, Time[Group == "CLEC"])
bootC <- bootstrap(CLEC, mean)
bootC
hist(bootC)
qqnorm(bootC)

Documentation reproduced from package resample, version 0.4, License: BSD_3_clause + file LICENSE

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