Regularization and Model Selection with Categorial Effect Modifiers

Gertheiss, Jan and Tutz, Gerhard (2010): Regularization and Model Selection with Categorial Effect Modifiers. Department of Statistics: Technical Reports, No.73 Statistica Sinica (to appear)

Abstract

The case of continuous effect modifiers in varying-coefficient models has been well investigated. Categorial effect modifiers, however, have been largely neglected. In this paper a regularization technique is proposed that allows for selection of covariates and fusion of categories of categorial effect modifiers in a linear model. It is distinguished between nominal and ordinal variables, since for the latter more economic parametrizations are warranted. The proposed methods are illustrated and investigated in simulation studies and real world data evaluations. Moreover, some asymptotic properties are derived. The paper is a preprint of an article that has been accepted for publication in Statistica Sinica. Please use the journal version for citation.

• Item Type: Paper
• Keywords: Categorial Predictors, Fused Lasso, Linear Model, Variable Selection, Varying-Coefficient Models
• Faculties: Mathematics, Computer Science and Statistics > Statistics; Mathematics, Computer Science and Statistics > Statistics > Technical Reports
• Subjects: 500 Science > 500 Science
• Language: English