A Fast and Efficient Estimation of the Parameters of a Model of Accident Frequencies via an MM Algorithm
In this paper, we consider a multivariate statistical model of accident frequencies having a variable number of parameters and whose parameters are dependent and subject to box constraints and linear equality constraints. We design a minorization-maximization (MM) algorithm and an accelerated MM alg...
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| Format: | Article |
| Language: | English |
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Wiley
2023-01-01
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| Series: | Journal of Applied Mathematics |
| Online Access: | http://dx.doi.org/10.1155/2023/3377201 |
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| _version_ | 1832547948993445888 |
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| author | Issa Cherif Geraldo Edoh Katchekpele Tchilabalo Abozou Kpanzou |
| author_facet | Issa Cherif Geraldo Edoh Katchekpele Tchilabalo Abozou Kpanzou |
| author_sort | Issa Cherif Geraldo |
| collection | DOAJ |
| description | In this paper, we consider a multivariate statistical model of accident frequencies having a variable number of parameters and whose parameters are dependent and subject to box constraints and linear equality constraints. We design a minorization-maximization (MM) algorithm and an accelerated MM algorithm to compute the maximum likelihood estimates of the parameters. We illustrate, through simulations, the performance of our proposed MM algorithm and its accelerated version by comparing them to Newton-Raphson (NR) and quasi-Newton algorithms. The results suggest that the MM algorithm and its accelerated version are better in terms of convergence proportion and, as the number of parameters increases, they are also better in terms of computation time. |
| format | Article |
| id | doaj-art-ce70a5e7ea54460f81a43314b79ed85f |
| institution | Kabale University |
| issn | 1687-0042 |
| language | English |
| publishDate | 2023-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Applied Mathematics |
| spelling | doaj-art-ce70a5e7ea54460f81a43314b79ed85f2025-02-03T06:42:50ZengWileyJournal of Applied Mathematics1687-00422023-01-01202310.1155/2023/3377201A Fast and Efficient Estimation of the Parameters of a Model of Accident Frequencies via an MM AlgorithmIssa Cherif Geraldo0Edoh Katchekpele1Tchilabalo Abozou Kpanzou2Laboratoire d’AnalyseLaboratoire de Modélisation Mathématique et d’Analyse Statistique Décisionnelle (LaMMASD)Laboratoire de Modélisation Mathématique et d’Analyse Statistique Décisionnelle (LaMMASD)In this paper, we consider a multivariate statistical model of accident frequencies having a variable number of parameters and whose parameters are dependent and subject to box constraints and linear equality constraints. We design a minorization-maximization (MM) algorithm and an accelerated MM algorithm to compute the maximum likelihood estimates of the parameters. We illustrate, through simulations, the performance of our proposed MM algorithm and its accelerated version by comparing them to Newton-Raphson (NR) and quasi-Newton algorithms. The results suggest that the MM algorithm and its accelerated version are better in terms of convergence proportion and, as the number of parameters increases, they are also better in terms of computation time.http://dx.doi.org/10.1155/2023/3377201 |
| spellingShingle | Issa Cherif Geraldo Edoh Katchekpele Tchilabalo Abozou Kpanzou A Fast and Efficient Estimation of the Parameters of a Model of Accident Frequencies via an MM Algorithm Journal of Applied Mathematics |
| title | A Fast and Efficient Estimation of the Parameters of a Model of Accident Frequencies via an MM Algorithm |
| title_full | A Fast and Efficient Estimation of the Parameters of a Model of Accident Frequencies via an MM Algorithm |
| title_fullStr | A Fast and Efficient Estimation of the Parameters of a Model of Accident Frequencies via an MM Algorithm |
| title_full_unstemmed | A Fast and Efficient Estimation of the Parameters of a Model of Accident Frequencies via an MM Algorithm |
| title_short | A Fast and Efficient Estimation of the Parameters of a Model of Accident Frequencies via an MM Algorithm |
| title_sort | fast and efficient estimation of the parameters of a model of accident frequencies via an mm algorithm |
| url | http://dx.doi.org/10.1155/2023/3377201 |
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