pseudo.v {asbio} | R Documentation |
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.
pseudo.v(data, statistic, order = 1, matrix = FALSE)
data |
A vector |
statistic |
A function whose output is a statistic (e.g. a sample mean). The function must have only one argument, a call to |
order |
The order of jackknifing to be used. |
matrix |
A logical statement. If |
In the first order jackknife procedure a statistic \hat{θ} is calculated using all n samples, it is then calculated with the first observation removed \hat{θ}_{-1}, with only the second observation removed, \hat{θ}_{-2}, and so on. This process is repeated for all n samples. The resulting vector of size n contains pseudovalues for their respective observations.
A vector of first-order jackknife pseudovalues is returned.
Ken Aho
Manly, B. F. J. (1997) Randomization and Monte Carlo Methods in Biology, 2nd edition. Chapman and Hall, London.
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)