Validation tests for semi-parametric models

Meintanis, Simos; Einbeck, Jochen

doi:10.1080/00949655.2013.806922

Validation tests for semi-parametric models

Meintanis, Simos; Einbeck, Jochen

Authors

Simos Meintanis

Professor Jochen Einbeck jochen.einbeck@durham.ac.uk
Professor

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.

Files

Accepted Journal Article (253 Kb)
PDF

Copyright Statement
This is an Accepted Manuscript of an article published by Taylor & Francis Group in Journal of Statistical Computation and Simulation on 18/06/2013, available online at: http://www.tandfonline.com/10.1080/00949655.2013.806922.