Package: jackknifeR 2.0.0

jackknifeR: Delete-d Jackknife for Point and Interval Estimation

This function generates jackknife samples by systematically leaving out d observations from the original dataset. It performs statistical estimation on each jackknife sample and computes jackknife statistics, including coefficients, bias correction, standard errors, and confidence intervals. \n The methodology builds upon the foundational work of Quenouille (1956) <doi:10.2307/2332914> and Tukey (1958) <doi:10.1214/aoms/1177706647> with extensions for dependent data following Shi (1988) <doi:10.1016/0167-7152(88)90011-9>

Authors:S. Mohanasundaram [aut, cre]

jackknifeR_2.0.0.tar.gz
jackknifeR_2.0.0.zip(r-4.7-any)jackknifeR_2.0.0.zip(r-4.6-any)jackknifeR_2.0.0.zip(r-4.5-any)
jackknifeR_2.0.0.tgz(r-4.6-any)jackknifeR_2.0.0.tgz(r-4.5-any)
jackknifeR_2.0.0.tar.gz(r-4.7-any)jackknifeR_2.0.0.tar.gz(r-4.6-any)
jackknifeR_2.0.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
jackknifeR/json (API)

# Install 'jackknifeR' in R:
install.packages('jackknifeR', repos = c('https://mohanasundarams.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/mohanasundarams/jackknifer/issues

On CRAN:

Conda:

2.70 score 1 stars 6 scripts 461 downloads 4 exports 10 dependencies

Last updated from:f43dff4b36. Checks:7 NOTE, 2 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develNOTE103
source / vignettesOK155
linux-releaseNOTE100
macos-releaseNOTE178
macos-oldrelNOTE147
windows-develNOTE62
windows-releaseNOTE69
windows-oldrelNOTE80
wasm-releaseOK74

Exports:jackknifejackknife.corjackknife.lmjackknife.lm.weighted

Dependencies:codetoolsdigestdoFutureforeachfuturefuture.applyglobalsiteratorslistenvparallelly