pseudo.v {asbio} | R Documentation |
The function returns first-order jackknife pseudovalues which can be used to create jackknife 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, matrix = FALSE)
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 . |
matrix |
A logical statement. If matrix = TRUE then rows in the matrix are sampled as multivariate observations. |
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.
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.
library(vegan) data(varespec) site18<-data.frame(t(varespec[1,][1:20]))# A partial set of observations from a single plot for a Scandinavian moss/vascular plant/lichen survey #Shannon-Weiner diversity SW<-function(data){ d<-data[data!=0] p<-d/sum(d) -1*sum(p*log(p)) } pv<-pseudo.v(site18,SW)