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Open AccessArticle10.32614/rj-2010-007

glmperm: A Permutation of Regressor Residuals Test for Inference in Generalized Linear Models

Wiebke Werft,Axel Benner-2010-01-01-The R Journal
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TL;DRAbstract

We introduce a new R package called glmperm for inference in generalized linear models especially for small and moderate-sized data sets. The inference is based on the permutation of regressor residuals test introduced by Potter ( The implementation of glmperm outperforms currently available permutation test software as glmperm can be applied in situations where more than one covariate is involved.

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We introduce a new R package called glmperm for inference in generalized linear models especially for small and moderate-sized data sets. The inference is based on the permutation of regressor residuals test introduced by Potter ( The implementation of glmperm outperforms currently available permutation test software as glmperm can be applied in situations where more than one covariate is involved.

Keywords

InferenceCovariateGeneralized linear modelPermutation (music)ResamplingStatisticsComputer scienceLinear model

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