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 |

`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 |

### 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.

### See Also

### 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*version 1.9-7 Index]