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)jackknifeR_2.0.0.zip(r-4.6)jackknifeR_2.0.0.zip(r-4.5)
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
card.svg |card.png
jackknifeR/json (API)
NEWS

# 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 7 scripts 659 downloads 4 exports 10 dependencies

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

TargetResultTimeFilesSyslog
linux-devel-x86_64NOTE106
source / vignettesOK167
linux-release-x86_64NOTE139
macos-release-arm64NOTE150
macos-oldrel-arm64NOTE148
windows-develNOTE88
windows-releaseNOTE89
windows-oldrelNOTE87
wasm-releaseOK87

Exports:jackknifejackknife.corjackknife.lmjackknife.lm.weighted

Dependencies:codetoolsdigestdoFutureforeachfuturefuture.applyglobalsiteratorslistenvparallelly