MDL mean function selection in semiparametric kernel regression models

Authors
Publication date 2008
Journal Communications in Statistics: Theory and Methods
Volume | Issue number 37 | 14
Pages (from-to) 2237-2248
Number of pages 12
Organisations
  • Faculty of Economics and Business (FEB) - Amsterdam School of Economics Research Institute (ASE-RI)
Abstract We study the problem of selecting the optimal functional form among a set of non nested, nonlinear mean functions for a semiparametric kernel based regression model. To this end we consider Rissanen's minimum description length (MDL) principle. We prove the consistency of the proposed MDL criterion. Its performance is examined via simulated data sets of univariate and bivariate nonlinear regression models.
Document type Article
Published at https://doi.org/10.1080/03610920701875267
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