Validation tests for semi-parametric models

Meintanis, Simos; Einbeck, Jochen

Abstract

Tests are proposed for validation of the hypothesis that a partial linear regression model adequately describes the structure of a given data set. The test statistics are formulated following the approach of Fourier-type conditional expectations first suggested by Bierens [Consistent model specification tests. J Econometr. 1982;20:105–134]. The proposed procedures are computationally convenient, and under fairly mild conditions lead to consistent tests. Corresponding bootstrap versions are compared with alternative procedures for a wide selection of different estimators of the underlying partial linear model.

Citation

Meintanis, S., & Einbeck, J. (2013). Validation tests for semi-parametric models. Journal of Statistical Computation and Simulation, 85(1), 131-146. https://doi.org/10.1080/00949655.2013.806922

• Journal Article Type: Article
• Acceptance Date: May 16, 2013
• Online Publication Date: Jun 18, 2013
• Publication Date: Jun 18, 2013
• Deposit Date: Sep 13, 2013
• Publicly Available Date: Apr 16, 2014
• Journal: Journal of Statistical Computation and Simulation
• Print ISSN: 0094-9655
• Electronic ISSN: 1563-5163
• Publisher: Taylor and Francis Group
• Peer Reviewed: Peer Reviewed
• Volume: 85
• Issue: 1
• Pages: 131-146
• DOI: https://doi.org/10.1080/00949655.2013.806922
• Keywords: Semi-linear model, Goodness-of-fit test, Empirical characteristic function, Bootstrap test.
• Public URL: https://durham-repository.worktribe.com/output/1478144