Bootstrap in Linear Models
Overview
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.
Install
Health
- OK13 OK2026-08-05
- NOTE12 OK, 1 NOTE2026-08-01
- OK14 OK2026-03-10
Documentation
- Help pages
- 7includes a package overview page
- Examples that run
- 100%7 run in a plain check
- Exported functions with examples
- 100%
- Documented parameters
- not tracked
- Return-value docs
- not tracked
- Help pages citing references
- 100%
Downloads
Dependencies
Installing lmboot adds 1 package (1 with compiled code, 898 KB of source tarballs). Heaviest: evd 898 KB.
Code & Tests
People & History
- RR 4.6.0 released · 2026-04-24
- RR 4.5.0 released · 2025-04-11
- RR 4.4.0 released · 2024-04-24
- RR 4.3.0 released · 2023-04-21
- RR 4.2.0 released · 2022-04-22
- RR 4.1.0 released · 2021-05-18
- RR 4.0.0 released · 2020-04-24
- 0.0.1Latest2019-06-03 · current release
- RR 3.6.0 released · 2019-04-26
Package metadata
- First published
- 2019-06-03
- Total releases
- 1 / 7 yrs
- License
- GPL-2 OSI
- Minimum R
- ≥ 3.5.0
- Download size
- 16 KB
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