Estimation in the Birnbaum-Saunders distribution based on scale-mixture of normals and the EM-algorithm

Título inglés	Estimation in the Birnbaum-Saunders distribution based on scale-mixture of normals and the EM-algorithm
Autor/es	N. Balakrishnan, Víctor Leiva, Antonio Sanhueza, Filidor Edilfonso Vilca Labra
Revista	1696-2281
Publicación	2009, 33 (2): 171-192
Tipo de documento	articulo
Idioma	Inglés
Resumen inglés	Scale mixtures of normal (SMN) distributions are used for modeling symmetric data. Members of this family have appealing properties such as robust estimates, easy number generation, and efficient computation of the ML estimates via the EM-algorithm. The Birnbaum-Saunders (BS) distribution is a positively skewed model that is related to the normal distribution and has received considerable attention. We introduce a type of BS distributions based on SMN models, produce a lifetime analysis, develop the EM-algorithm for ML estimation of parameters, and illustrate the obtained results with real data showing the robustness of the estimation procedure.
Palabras clave inglés	Birnbaum-Saunders distribution, EM-algorithm, kurtosis, maximum likelihood methods, robust estimation, scale mixtures of normal distributions.
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