期刊名称：Electronic Journal of Applied Statistical Analysis
电子版ISSN：2070-5948
出版年度：2019
卷号：12
期号：1
页码：26-43
DOI：10.1285/i20705948v12n1p26
出版社：University of Salento
摘要：Birnbaum-Saunders (BS) distribution is a model with positive domain that
is used in many fields including reliability and environmental studies. This
article introduces a generalized version of the BS distribution which arises
from the shape mixture of skew-normal distribution. A feasible EM type
algorithm is developed to obtain maximum likelihood (ML) estimates of parameters
of the new model. The asymptotic standard errors of ML estimates
are obtained via the information-based approximation. The robustness and
application of the proposed methodology are illustrated through simulation
studies and air pollution analysis.
其他摘要：Birnbaum-Saunders (BS) distribution is a model with positive domain thatis used in many fields including reliability and environmental studies. Thisarticle introduces a generalized version of the BS distribution which arisesfrom the shape mixture of skew normal distribution. A feasible EM typealgorithm is developed to obtain maximum likelihood (ML) estimates of pa-rameters of the new model. The asymptotic standard errors of ML estimatesare obtained via the information-based approximation. The robustness andapplication of the proposed methodology is illustrated through simulationstudies and air pollution analysis.
关键词：ECM algorithm; Observed information matrix; Robustness;
Shape mixtures.
