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Lookup NU author(s): Dr Jian Shi
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In this work, we develop some diagnostics for nonlinear regression model with scale mixtures of skew-normal (SMSN) and first-order autoregressive errors. The SMSN distribution class covers symmetric as well as asymmetric and heavy-tailed distributions, which offers a more flexible framework for modelling. Maximum-likelihood (ML) estimates are computed via an expectation-maximization-type algorithm. Local influence diagnostics and score test for the correlation are also derived. The performances of the ML estimates and the test statistic are investigated through Monte Carlo simulations. Finally, a real data set is used to illustrate our diagnostic methods.
Author(s): Cao CZ, Lin JG, Shi JQ
Publication type: Article
Publication status: Published
Print publication date: 01/09/2014
Online publication date: 30/05/2013
Acceptance date: 21/11/2012
ISSN (print): 0233-1888
ISSN (electronic): 1029-4910
Publisher: Taylor & Francis
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