pseudo.v {asbio} R Documentation

## Jacknife pseudo-values

### Description

The function returns jackknife pseudovalues which can then be used to create statistical summaries, e.g. the jackknife parameter estimate, and the jackknife standard error. The function can be run on univariate data (matrix = FALSE) or multivariate data (matrix =TRUE). In the later case matrix rows are treated as multivariate observations.

### Usage

pseudo.v(data, statistic, order = 1, matrix = FALSE)


### Arguments

 data A vector (matrix =FALSE) or matrix (matrix=TRUE) of quantitative data. statistic A function whose output is a statistic (e.g. a sample mean). The function must have only one argument, a call to data. order The order of jackknifing to be used. matrix A logical statement. If matrix = TRUE then rows in the matrix are sampled as multivariate observations.

### Details

In the first order jackknife procedure a statistic \hat{\theta} is calculated using all n samples, it is then calculated with the first observation removed \hat{\theta}_{-1}, with only the second observation removed, \hat{\theta}_{-2}, and so on. This process is repeated for all n samples. The resulting vector of size n contains pseudovalues for their respective observations.

### Value

A vector of first-order jackknife pseudovalues is returned.

Ken Aho

### References

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

empinf, boot, bootstrap

### Examples

data(cliff.sp)
siteCD1<-data.frame(t(cliff.sp[1,]))

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

pv<-pseudo.v(siteCD1,SW)


[Package asbio version 1.9-7 Index]