jackknife {bootstrap} | R Documentation |
See Efron and Tibshirani (1993) for details on this function.
jackknife(x, theta, ...)
x |
a vector containing the data. To jackknife more complex data structures (e.g. bivariate data) see the last example below. |
theta |
function to be jackknifed. Takes |
... |
any additional arguments to be passed to |
list with the following components
jack.se |
The jackknife estimate of standard error of |
jack.bias |
The jackknife estimate of bias of |
jack.values |
The n leave-one-out values of |
call |
The deparsed call |
Efron, B. and Tibshirani, R. (1986). The Bootstrap Method for standard errors, confidence intervals, and other measures of statistical accuracy. Statistical Science, Vol 1., No. 1, pp 1-35.
Efron, B. and Tibshirani, R. (1993) An Introduction to the Bootstrap. Chapman and Hall, New York, London.
# jackknife values for the sample mean # (this is for illustration; # since "mean" is a # built in function, jackknife(x,mean) would be simpler!) x <- rnorm(20) theta <- function(x){mean(x)} results <- jackknife(x,theta) # To jackknife functions of more complex data structures, # write theta so that its argument x # is the set of observation numbers # and simply pass as data to jackknife the vector 1,2,..n. # For example, to jackknife # the correlation coefficient from a set of 15 data pairs: xdata <- matrix(rnorm(30),ncol=2) n <- 15 theta <- function(x,xdata){ cor(xdata[x,1],xdata[x,2]) } results <- jackknife(1:n,theta,xdata)