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>.

Package details

AuthorMegan Heyman [aut, cre]
MaintainerMegan Heyman <[email protected]>
LicenseGPL-2
Version0.0.1
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("lmboot")

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lmboot documentation built on June 3, 2019, 5:03 p.m.