SECOND-ORDER ASYMPTOTICS FOR SCORE TESTS IN HETEROSKEDASTIC t REGRESSION MODELS

This paper develops corrected score tests for heteroskedastic t regression models, thus generalizing results by Cordeiro, Ferrari and Paula [1] and Cribari-Neto and Ferrari [2] for normal regression models and by Ferrari and Arellano-Valle [3] for homoskedastic t regression models. We present, in ma...

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Bibliographic Details
Published in:Communications in statistics. Theory and methods 2002-08, Vol.31 (9), p.1515-1529
Main Authors: Barroso, Lúcia P., Cordeiro, Gauss M., Vasconcellos, Klaus L. P.
Format: Article
Language:English
Subjects:
Bartlett-type correction
Chi-squared distribution
Dispersion parameter
Exact sciences and technology
Heteroskedastic model
Linear inference, regression
Link function
Mathematics
Maximum likelihood estimate
Numerical analysis
Numerical analysis. Scientific computation
Numerical methods in probability and statistics
Probability and statistics
Sciences and techniques of general use
Statistics
Student t model
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Summary:This paper develops corrected score tests for heteroskedastic t regression models, thus generalizing results by Cordeiro, Ferrari and Paula [1] and Cribari-Neto and Ferrari [2] for normal regression models and by Ferrari and Arellano-Valle [3] for homoskedastic t regression models. We present, in matrix notation, Bartlett-type correction formulae to improve score tests in this class of models. The corrected score statistics have a chi-squared distribution to order n −1 , where n is the sample size. We apply our main result to a few special models and present simulation results comparing the performance of the usual score tests and their corrected versions.
ISSN:0361-0926
1532-415X
DOI:10.1081/STA-120013009