Semiparametric approximation methods in multivariate model selection

Jiti Gao, Rodney Wolff, Vo Anh

Research output: Contribution to journalArticleResearchpeer-review

8 Citations (Scopus)


In this paper we propose a cross-validation selection criterion to determine asymptotically the correct model among the family of all possible partially linear models when the underlying model is a partially linear model. We establish the asymptotic consistency of the criterion. In addition, the criterion is illustrated using two real sets of data.

Original languageEnglish
Pages (from-to)754-772
Number of pages19
JournalJournal of Complexity
Issue number4
Publication statusPublished - 1 Jan 2001


  • Dimensional reduction
  • Linear regression
  • Model selection
  • Nonlinear regression
  • Nonlinear time series
  • Nonparametric regression
  • Semiparametric regression

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