asbio (version 0.2-1)

bootstrap: 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, 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.

matrix

A logical statement. If matrix = TRUE then rows in the matrix are sampled as multivariate observations.

Value

• Returns a bootstrap distribution of a statistic.

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.

References

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

See Also

boot

Examples

library(vegan)
data(varespec)
# A partial set of observations from a single plot for a Scandinavian moss/vascular plant/lichen survey.
site18<-data.frame(t(varespec[1,][1:20]))

#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)