asbio (version 1.9-2)

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 = 1000, prob = NULL, matrix = FALSE)

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.

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.

Author

Ken Aho

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, ci.boot

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)