Semnan University International Journal of Nonlinear Analysis and Applications 2008-6822 13 1 2022 03 01 Bayesian parameter estimation in addiction model 3059 3071 6042 10.22075/ijnaa.2022.6042 EN Najla A. AL-Khairullah Department of Mathematics, College of Science, University of Baghdad, Iraq Tasnim Hasan Kadhim AlBaldawi Department of Mathematics, College of Science, University of Baghdad, Iraq Journal Article 2021 12 01 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.  https://ijnaa.semnan.ac.ir/article_6042_1d4f901349b2c4c0684dff60d06ae7ce.pdf