Department of Economics and Business Economics

Additive regression splines with irrelevant categorical and continuous regressors

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  • S. Ma, University of California at Riverside
  • ,
  • J.S. Racine
We consider the problem of estimating a relationship using semiparametric additive regression splines when there exist both continuous and categorical regressors, some of which are irrelevant but this is not known a priori. We show that choosing the spline degree, number of subintervals, and bandwidths via cross-validation can automatically remove irrelevant regressors, thereby delivering 'automatic dimension reduction' without the need for pre-testing. Theoretical underpinnings are provided, finite-sample performance is studied, and an illustrative application demonstrates the efficacy of the proposed approach in finite-sample settings. An R package implementing the methods is available from the Comprehensive R Archive Network (Racine and Nie (2011)).
Original languageEnglish
JournalStatistica Sinica
Pages (from-to)515-541
Number of pages27
Publication statusPublished - 1 Apr 2013

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