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) , the residual and paired bootstraps by Efron (1979, ISBN:978-1-4612-4380-9), the delete-1 jackknife by Quenouille (1956) , and the Bayesian bootstrap by Rubin (1981) .


Reference manual

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install.packages("lmboot")

0.0.1 by Megan Heyman, 7 years ago


Browse source code at https://github.com/cran/lmboot


Authors: Megan Heyman [aut, cre]


Documentation:   PDF Manual  


GPL-2 license


Imports evd, stats


Suggested by skedastic.


See at CRAN