bootstrap {asbio} 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.

Ken Aho

### References

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

`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)
```

[Package asbio version 1.7 Index]