Flexible Parsimonious Mixture of Skew Factor Analysis Based on Normal Mean--Variance Birnbaum-Saunders
The purpose of this paper is to extend the mixture factor analyzers (MFA) model \CG{to handle} missing and heavy-\CG{tailed} data. In this model, the distribution of factors loading and errors arise from the multivariate normal mean-variance mixture of \CG{the} Birnbaum-Saunders (NMVBS) distri...
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| Language: | English |
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University of Kashan
2024-12-01
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| Series: | Mathematics Interdisciplinary Research |
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| Online Access: | https://mir.kashanu.ac.ir/article_114583_c88b79e69d0b72add6e7b3c494bd06c5.pdf |
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| author | Farzane Hashemi Jalal Askari Saeed Darijani |
| author_facet | Farzane Hashemi Jalal Askari Saeed Darijani |
| author_sort | Farzane Hashemi |
| collection | DOAJ |
| description | The purpose of this paper is to extend the mixture factor analyzers (MFA) model \CG{to handle} missing and heavy-\CG{tailed} data. In this model, the distribution of factors loading and errors arise from the multivariate normal mean-variance mixture of \CG{the} Birnbaum-Saunders (NMVBS) distribution. By using the structures covariance matrix, we introduce parsimonious MFA based on NMVBS distribution. An Expectation Maximization (EM)-type algorithm is developed for parameter estimation. Simulations study and real data sets represent the efficiency and performance of the proposed model. |
| format | Article |
| id | doaj-art-f56de2a0fd6e45e581762a917d1de55c |
| institution | Kabale University |
| issn | 2476-4965 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | University of Kashan |
| record_format | Article |
| series | Mathematics Interdisciplinary Research |
| spelling | doaj-art-f56de2a0fd6e45e581762a917d1de55c2024-12-14T05:32:56ZengUniversity of KashanMathematics Interdisciplinary Research2476-49652024-12-019438541110.22052/mir.2024.254416.1459114583Flexible Parsimonious Mixture of Skew Factor Analysis Based on Normal Mean--Variance Birnbaum-SaundersFarzane Hashemi0Jalal Askari1Saeed Darijani2Department of Statistics, University of Kashan, Kashan, I. R. IranDepartment of Applied Mathematics, University of Kashan,Kashan, I. R. IranFarhangian University Of Kerman, Kerman, I. R. IranThe purpose of this paper is to extend the mixture factor analyzers (MFA) model \CG{to handle} missing and heavy-\CG{tailed} data. In this model, the distribution of factors loading and errors arise from the multivariate normal mean-variance mixture of \CG{the} Birnbaum-Saunders (NMVBS) distribution. By using the structures covariance matrix, we introduce parsimonious MFA based on NMVBS distribution. An Expectation Maximization (EM)-type algorithm is developed for parameter estimation. Simulations study and real data sets represent the efficiency and performance of the proposed model.https://mir.kashanu.ac.ir/article_114583_c88b79e69d0b72add6e7b3c494bd06c5.pdfnormal mean-variance distributionem-type algorithmfactor analysisheavy-tailstrongly leptokurtic |
| spellingShingle | Farzane Hashemi Jalal Askari Saeed Darijani Flexible Parsimonious Mixture of Skew Factor Analysis Based on Normal Mean--Variance Birnbaum-Saunders Mathematics Interdisciplinary Research normal mean-variance distribution em-type algorithm factor analysis heavy-tail strongly leptokurtic |
| title | Flexible Parsimonious Mixture of Skew Factor Analysis Based on Normal Mean--Variance Birnbaum-Saunders |
| title_full | Flexible Parsimonious Mixture of Skew Factor Analysis Based on Normal Mean--Variance Birnbaum-Saunders |
| title_fullStr | Flexible Parsimonious Mixture of Skew Factor Analysis Based on Normal Mean--Variance Birnbaum-Saunders |
| title_full_unstemmed | Flexible Parsimonious Mixture of Skew Factor Analysis Based on Normal Mean--Variance Birnbaum-Saunders |
| title_short | Flexible Parsimonious Mixture of Skew Factor Analysis Based on Normal Mean--Variance Birnbaum-Saunders |
| title_sort | flexible parsimonious mixture of skew factor analysis based on normal mean variance birnbaum saunders |
| topic | normal mean-variance distribution em-type algorithm factor analysis heavy-tail strongly leptokurtic |
| url | https://mir.kashanu.ac.ir/article_114583_c88b79e69d0b72add6e7b3c494bd06c5.pdf |
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