Package: lmboot 0.0.1
lmboot: Bootstrap in Linear Models
Various efficient and robust bootstrap methods are implemented for linear models with least squares estimation. Functions within this package allow users to create bootstrap sampling distributions for model parameters, test hypotheses about parameters, and visualize the bootstrap sampling or null distributions. Methods implemented for linear models include the wild bootstrap by Wu (1986) <doi:10.1214/aos/1176350142>, the residual and paired bootstraps by Efron (1979, ISBN:978-1-4612-4380-9), the delete-1 jackknife by Quenouille (1956) <doi:10.2307/2332914>, and the Bayesian bootstrap by Rubin (1981) <doi:10.1214/aos/1176345338>.
Authors:
lmboot_0.0.1.tar.gz
lmboot_0.0.1.zip(r-4.5)lmboot_0.0.1.zip(r-4.4)lmboot_0.0.1.zip(r-4.3)
lmboot_0.0.1.tgz(r-4.4-any)lmboot_0.0.1.tgz(r-4.3-any)
lmboot_0.0.1.tar.gz(r-4.5-noble)lmboot_0.0.1.tar.gz(r-4.4-noble)
lmboot_0.0.1.tgz(r-4.4-emscripten)lmboot_0.0.1.tgz(r-4.3-emscripten)
lmboot.pdf |lmboot.html✨
lmboot/json (API)
| # Install 'lmboot' in R: |
| install.packages('lmboot', repos = c('https://meganheyman.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/meganheyman/lmboot/issues
Last updated 5 years agofrom:1d8b62c48d. Checks:OK: 7. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 01 2024 |
| R-4.5-win | OK | Nov 01 2024 |
| R-4.5-linux | OK | Nov 01 2024 |
| R-4.4-win | OK | Nov 01 2024 |
| R-4.4-mac | OK | Nov 01 2024 |
| R-4.3-win | OK | Nov 01 2024 |
| R-4.3-mac | OK | Nov 01 2024 |
Exports:ANOVA.bootbayesian.bootjackknifepaired.bootresidual.bootwild.boot
Dependencies:evd
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Bootstrap in Linear Models | lmboot-package lmboot |
| Residual and wild bootstrap in 1-way and 2-way ANOVA | ANOVA.boot |
| Bayesian Bootstrap in Linear Models | bayesian.boot |
| Delete-1 Jackknife in Linear Models | jackknife |
| Paired Bootstrap in Linear Models | paired.boot |
| Residual bootstrap in linear models | residual.boot |
| Wild Bootstrap in Linear Models | wild.boot |
