MDL mean function selection in semiparametric kernel regression models
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| 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 |
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| 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
(Final published version)
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