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Bayesian parameter estimation in addiction model | ||
| International Journal of Nonlinear Analysis and Applications | ||
| مقاله 247، دوره 13، شماره 1، خرداد 2022، صفحه 3059-3071 اصل مقاله (982.44 K) | ||
| نوع مقاله: Research Paper | ||
| شناسه دیجیتال (DOI): 10.22075/ijnaa.2022.6042 | ||
| نویسندگان | ||
| Najla A. AL-Khairullah* ؛ Tasnim Hasan Kadhim AlBaldawi | ||
| Department of Mathematics, College of Science, University of Baghdad, Iraq | ||
| تاریخ دریافت: 10 آذر 1400، تاریخ بازنگری: 09 دی 1400، تاریخ پذیرش: 13 دی 1400 | ||
| چکیده | ||
| In this paper, we investigated the performance of Bayesian Computational methods for estimating the parameters of the multinomial Logistic regression model. We discussed two of the most common Bayesian computational algorithms: the Random walk Metropolis-Hastings (RWM) and Slice algorithms and their application to estimating the parameters of the addiction model as well as comparing the performance of these algorithms using the mean square error (MSE) criterion. The results revealed that the performance of the algorithms is excellent, with a slight superiority to the RWM algorithm. | ||
| کلیدواژه‌ها | ||
| Multinomial Logistic Regression؛ MCMC؛ Random Walk Metropolis-Hasting Algorithm؛ Slice Sampling | ||
| مراجع | ||
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