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 |
... |
Optional additional arguments for the |
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")