Statistical Diagnostics for Skew-t-Normal Nonlinear Models

This work develops diagnostics for skew-t-normal nonlinear models which provides an useful extension for ordinary normal regression models when the data set under consideration involves heavy tail and asymmetric outcomes. The case-deletion model (CDM) is considered, and several diagnostic measures a...

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Bibliographic Details
Published in:Communications in statistics. Simulation and computation 2009-11, Vol.38 (10), p.2096-2110
Main Authors: Lin, Jin-Guan, Xie, Feng-Chang, Wei, Bo-Cheng
Format: Article
Language:English
Subjects:
Case-deletion model
Distribution theory
Exact sciences and technology
Homogeneity
Linear inference, regression
Mathematics
Nonlinear regression models
Nonparametric inference
Numerical analysis
Numerical analysis. Scientific computation
Numerical methods in probability and statistics
Probability and statistics
Sciences and techniques of general use
Score test
Simulation studies
Skew-t-normal distribution
Statistics
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Summary:This work develops diagnostics for skew-t-normal nonlinear models which provides an useful extension for ordinary normal regression models when the data set under consideration involves heavy tail and asymmetric outcomes. The case-deletion model (CDM) is considered, and several diagnostic measures are derived and discussed. Furthermore, we discuss score test for homogeneity of the variance in skew-t-normal nonlinear models. The ultrasonic calibration data are illustrated our methodology and the properties of score test statistic are investigated through Monte Carlo simulation.
ISSN:0361-0918
1532-4141
DOI:10.1080/03610910903249502