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A skew factor analysis model based on the normal mean–variance mixture of Birnbaum–Saunders distribution |
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| Authors: | Farzane Hashemi Mehrdad Naderi Ahad Jamalizadeh Tsung-I Lin |
| Institution: | aDepartment of Statistics, Faculty of Mathematics and Computer, Shahid Bahonar University of Kerman, Kerman, Iran;bDepartment of Statistics, Faculty of Natural & Agricultural Sciences, University of Pretoria, Pretoria, South Africa;cInstitute of Statistics, National Chung Hsing University, Taichung, Taiwan;dDepartment of Public Health, China Medical University, Taichung, Taiwan |
| Abstract: | This paper presents a robust extension of factor analysis model by assuming the multivariate normal mean–variance mixture of Birnbaum–Saunders distribution for the unobservable factors and errors. A computationally analytical EM-based algorithm is developed to find maximum likelihood estimates of the parameters. The asymptotic standard errors of parameter estimates are derived under an information-based paradigm. Numerical merits of the proposed methodology are illustrated using both simulated and real datasets. |
| Keywords: | Birnbaum– Saunders distribution EM algorithm factor analysis skewness outliers |