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Penalized regression with individual deviance effects

Perperoglou, Aris and Eilers, Paul HC (2010) 'Penalized regression with individual deviance effects.' Computational Statistics, 25 (2). pp. 341-361. ISSN 0943-4062

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The present work addresses the problem of model estimation and computations for discrete data when some covariates are modeled smoothly using splines. We propose to introduce and explicitly estimate individual deviance effects (one for each observation), constrained by a ridge penalty. This turns out to be an effective way to absorb model excess variation and detect systematic patterns. Large but very sparse systems of penalized likelihood equations have to be solved. We present fast and compact algorithms for fitting, estimation and computation of the effective dimension. Applications to counts, binomial, and survival data illustrate practical use of this model. © The Author(s) 2009.

Item Type: Article
Uncontrolled Keywords: Generalized linear models; Smoothing; Effective dimension; Penalized regression
Subjects: Q Science > QA Mathematics
Divisions: Faculty of Science and Health
Faculty of Science and Health > Mathematical Sciences, Department of
SWORD Depositor: Elements
Depositing User: Elements
Date Deposited: 06 Nov 2012 11:01
Last Modified: 15 Jan 2022 00:46

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