Description Usage Arguments Value References Examples

See Efron and Tibshirani (1993) for details on this function.

1 |

`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.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 | ```
# 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)
``` |

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