Heteroscedastic nonlinear regression models based on scale mixtures of skew-normal distributions |
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Authors: | Lachos Victor H Bandyopadhyay Dipankar Garay Aldo M |
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Affiliation: | a Departamento de Estatística, Universidade Estatual de Campinas, Brazilb Division of Biostatistics and Epidemiology, Medical University of South Carolina, USA |
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Abstract: | An extension of some standard likelihood based procedures to heteroscedastic nonlinear regression models under scale mixtures of skew-normal (SMSN) distributions is developed. We derive a simple EM-type algorithm for iteratively computing maximum likelihood (ML) estimates and the observed information matrix is derived analytically. Simulation studies demonstrate the robustness of this flexible class against outlying and influential observations, as well as nice asymptotic properties of the proposed EM-type ML estimates. Finally, the methodology is illustrated using an ultrasonic calibration data. |
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Keywords: | EM algorithm Homogeneity Nonlinear regression models Scale mixtures Skew-normal |
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