jackFunc {boodd}R Documentation

Jackknife Variance Function

Description

Creates a vector-valued function for computing both the statistic defined by func and the estimated jackknife variance of the statistic.

Usage

jackFunc(func, ...)

Arguments

func

The function used to compute the statistic on each sample.

...

Optional additional arguments for the func function.

Details

The jackFunc function constructs a new function that, when applied to a data sample, calculates both the statistic specified by func and its associated jackknife variance. This newly created function is useful in generic bootstrap procedures, particularly for constructing bootstrap-t confidence intervals.

Value

Returns an object, which is a function.

References

Bertail, P. and Dudek, A. (2025). Bootstrap for Dependent Data, with an R package (by Bernard Desgraupes and Karolina Marek) - submitted.

Efron, B. (1979). Bootstrap methods: another look at the jackknife. Ann. Statist., 7, 1-26.

Gray, H., Schucany, W. and Watkins, T. (1972). The Generalized Jackknife Statistics. Marcel Dekker, New York.

Quenouille, M.H. (1949). Approximate tests of correlation in time-series. J. Roy. Statist. Soc., Ser. B, 11, 68-84.

See Also

jackVar, boots, jackVarBlock, jackFuncBlock, jackFuncRegen.

Examples

# Create a function to compute the empirical skewness
func <- function(x) { mean((x - mean(x))^3) / (mean((x - mean(x))^2)^(3/2)) }
x <- rnorm(100)
# Create a function to compute the empirical skewness and its variance
jf <- jackFunc(func)
# Bootstrapping of the skewness and its variance allows to construct 
# bootstrap-t confidence intervals
boo1 <- boots(x, jf, 299)
confint(boo1, method="all")

[Package boodd version 0.1 Index]