On bivariate Poisson regression models
In this paper, we consider estimating the parameters of bivariate and zero-inflated bivariate Poisson regression models using the conditional method. This method is compared with the standard method, which uses the joint probability function. Simulations and real applications show that the two metho...
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| Format: | Article |
| Language: | English |
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Elsevier
2016-04-01
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| Series: | Journal of King Saud University: Science |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1018364715000798 |
| _version_ | 1818021698403827712 |
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| author | Fatimah E. AlMuhayfith Abdulhamid A. Alzaid Maha A. Omair |
| author_facet | Fatimah E. AlMuhayfith Abdulhamid A. Alzaid Maha A. Omair |
| author_sort | Fatimah E. AlMuhayfith |
| collection | DOAJ |
| description | In this paper, we consider estimating the parameters of bivariate and zero-inflated bivariate Poisson regression models using the conditional method. This method is compared with the standard method, which uses the joint probability function. Simulations and real applications show that the two methods have almost identical Akaike Information Criteria and parameter estimates, but the conditional method has a much faster execution time than the joint method. We conducted our computations using the R and SAS package. Our results also indicate that the execution time of SAS is faster than that of R. |
| first_indexed | 2024-04-14T08:21:12Z |
| format | Article |
| id | doaj.art-aee87ae794f44c2a926cb07c2bcd4a24 |
| institution | Directory Open Access Journal |
| issn | 1018-3647 |
| language | English |
| last_indexed | 2024-04-14T08:21:12Z |
| publishDate | 2016-04-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Journal of King Saud University: Science |
| spelling | doaj.art-aee87ae794f44c2a926cb07c2bcd4a242022-12-22T02:04:12ZengElsevierJournal of King Saud University: Science1018-36472016-04-0128217818910.1016/j.jksus.2015.09.003On bivariate Poisson regression modelsFatimah E. AlMuhayfith0Abdulhamid A. Alzaid1Maha A. Omair2Department of Mathematics and Statistics, King Faisal University, Saudi ArabiaDepartment of Statistics and Operations Research, King Saud University, Saudi ArabiaDepartment of Statistics and Operations Research, King Saud University, Saudi ArabiaIn this paper, we consider estimating the parameters of bivariate and zero-inflated bivariate Poisson regression models using the conditional method. This method is compared with the standard method, which uses the joint probability function. Simulations and real applications show that the two methods have almost identical Akaike Information Criteria and parameter estimates, but the conditional method has a much faster execution time than the joint method. We conducted our computations using the R and SAS package. Our results also indicate that the execution time of SAS is faster than that of R.http://www.sciencedirect.com/science/article/pii/S1018364715000798Correlated count dataConditional modelingBivariate Poisson distributionRegression modelsZero-inflated models |
| spellingShingle | Fatimah E. AlMuhayfith Abdulhamid A. Alzaid Maha A. Omair On bivariate Poisson regression models Journal of King Saud University: Science Correlated count data Conditional modeling Bivariate Poisson distribution Regression models Zero-inflated models |
| title | On bivariate Poisson regression models |
| title_full | On bivariate Poisson regression models |
| title_fullStr | On bivariate Poisson regression models |
| title_full_unstemmed | On bivariate Poisson regression models |
| title_short | On bivariate Poisson regression models |
| title_sort | on bivariate poisson regression models |
| topic | Correlated count data Conditional modeling Bivariate Poisson distribution Regression models Zero-inflated models |
| url | http://www.sciencedirect.com/science/article/pii/S1018364715000798 |
| work_keys_str_mv | AT fatimahealmuhayfith onbivariatepoissonregressionmodels AT abdulhamidaalzaid onbivariatepoissonregressionmodels AT mahaaomair onbivariatepoissonregressionmodels |