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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)
A vector of first-order jackknife pseudovalues is returned.
A vector (matrix =FALSE)
or matrix (matrix=TRUE)
of quantitative data.
A function whose output is a statistic (e.g. a sample mean). The function must have only one argument, a call to data
.
The order of jackknifing to be used.
A logical statement. If matrix = TRUE
then rows in the matrix are sampled as multivariate observations.
Ken Aho
In the first order jackknife procedure a statistic
Manly, B. F. J. (1997) Randomization and Monte Carlo Methods in Biology, 2nd edition. Chapman and Hall, London.
empinf
, boot
, bootstrap
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)
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