bootstrap: A simple function for bootstrapping
In asbio: A Collection of Statistical Tools for Biologists

bootstrap

R Documentation

A simple function for bootstrapping

Description

The function serves as a simplified alternative to the function boot from the library boot.

Usage

bootstrap(data, statistic, R = 1000, prob = NULL, matrix = FALSE)

Arguments

`data`	Raw data to be bootstrapped. A vector or quantitative data or a matrix if `matrix =TRUE`.
`statistic`	A function whose output is a statistic (e.g. a sample mean). The function must have only one argument, a call to data.
`R`	The number of bootstrap iterations.
`prob`	A vector of probability weights for paramteric bootstrapping.
`matrix`	A logical statement. If `matrix = TRUE` then rows in the matrix are sampled as multivariate observations.

Details

With bootstrapping we sample with replacement from a dataset of size n with n samples R times. At each of the R iterations a statistical summary can be created resulting in a bootstrap distribution of statistics.

Value

Returns a list. The utility function asbio:::print.bootstrap returns summary output. Invisible items include the resampling distribution of the statistic, the data, the statistic, and the bootstrap samples.

Author(s)

Ken Aho

References

Manly, B. F. J. (1997) Randomization and Monte Carlo Methods in Biology, 2nd edition. Chapman and Hall, London.

Examples



data(vs)
# A partial set of observations from a single plot for a Scandinavian 
# moss/vascular plant/lichen survey.
site18<-t(vs[1,])

#Shannon-Weiner diversity
SW<-function(data){
d<-data[data!=0]
p<-d/sum(d)
-1*sum(p*log(p))
}

bootstrap(site18[,1],SW,R=1000,matrix=FALSE)

asbio documentation built on May 29, 2024, 5:57 a.m.