Artículos de revistas
Heteroscedastic nonlinear regression models based on scale mixtures of skew-normal distributions
Registro en:
Statistics & Probability Letters. Elsevier Science Bv, v. 81, n. 8, n. 1208, n. 1217, 2011.
0167-7152
WOS:000292232700043
10.1016/j.spl.2011.03.019
Autor
Lachos, VH
Bandyopadhyay, D
Garay, AM
Institución
Resumen
Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) 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. (C) 2011 Elsevier B.V. All rights reserved. 81 8 1208 1217 Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) NIH/NCRR [P20 RR017696-06] Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) FAPESP [2010/012465] CNPq [201384/2008-6] NIH/NCRR [P20 RR017696-06]