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Regularization for Generalized Additive Mixed Models by Likelihood-Based Boosting

OBJECTIVE: With the emergence of semi- and nonparametric regression the generalized linear mixed model has been extended to account for additive predictors. However, available fitting methods fail in high dimensional settings where many explanatory variables are present. We extend the concept of boo...

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Main Authors: Groll, Andreas, Tutz, Gerhard
格式: Artigo
語言:Inglês
出版: 2012
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在線閱讀:https://ncbi.nlm.nih.gov/pmc/articles/PMC3644420/
https://ncbi.nlm.nih.gov/pubmed/22378253
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3414/ME11-02-0021
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