jackknife: Delete-d Jackknife for Estimates

Description

This function creates jackknife samples from the data by sequentially removing d observations from the data, and calculates the estimates by the specified function and its bias, standard error, and confidence intervals.

Usage

jackknife(statistic, d = 1, data, conf = 0.95, numCores = detectCores())

Value

A list containing a summary data frame of jackknife estimates with bias, standard error. t-statistics, and confidence intervals, estimate for the original sample and a data frame with estimates for jackknife samples.

Arguments

statistic: a function returning a vector of estimates to be passed to jackknife
d: Number of observations to be deleted from data to make jackknife samples. The default is 1 (for delete-1 jackknife).
data: Data frame with dependent and independent independent variables specified in the formula
conf: Confidence level, a positive number < 1. The default is 0.95.
numCores: Number of processors to be used

References

Quenouille, M. H. (1956). Notes on Bias in Estimation. Biometrika, 43(3/4), 353-360. tools:::Rd_expr_doi("10.2307/2332914")

Tukey, J. W. (1958). Bias and Confidence in Not-quite Large Samples. Annals of Mathematical Statistics, 29(2), 614-623. tools:::Rd_expr_doi("10.1214/aoms/1177706647")

Shi, X. (1988). A note on the delete-d jackknife variance estimators. Statistics & Probability Letters, 6(5), 341-347. tools:::Rd_expr_doi("10.1016/0167-7152(88)90011-9")

Examples

Run this code

## library(jackknifeR)
fn <- function(data){
   mod <- lm(speed~dist, data = data)
   return(coef(mod))}
jkn <- jackknife(statistic = fn, d = 2, data = cars, numCores= 2)
jkn