jackFuncRegen {boodd}R Documentation

Jackknife Variance Function for Markov Chains Using Regenerative Blocks

Description

Creates a function that calculates both a specified statistic and its jackknife variance estimator based on regenerative blocks for Markov chains.

Usage

jackFuncRegen(func, atom = atom, small = NULL, ...)

Arguments

func

A function for which the statistic and the jackknife variance are to be calculated.

atom

A numeric value or a string; an atom of the Markov chain..

small

An optional object of class smallEnsemble. It can be created optimally using findBestEpsilon.

...

Optional additional arguments for the func function.

Details

This function is designed for use with regenerative data, such as Markov chains. It employs regeneration-based methods to estimate the jackknife variance of a given statistic by omitting alternatively each block to compute the function of interest. This function is particularly useful in conjunction with functions like regenboot and provides an alternative to block-based methods like jackFuncBlock.

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.

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

See Also

jackVar, jackFunc, regenboot, jackVarBlock, jackFuncBlock.

Examples

x=genMM1(100,1,2)
#' # A function to compute the mean of strictly positive values and its variance based on
# regenerative blocks
func <- function(x) {mean(x*(x>0))}
jfb <- jackFuncRegen(func, atom=0)
# Regenerative bootstrap of the mean of strictly positive values and its variance allows
# to construct bootstrap-t confidence intervals
boo <- regenboot(x,jfb,99, atom=0)
confint(boo, method="all")

[Package boodd version 0.1 Index]