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Idea about using ordinary least square by centroid methods for fuzzy pure spatial autoregressive model | ||
| International Journal of Nonlinear Analysis and Applications | ||
| مقاله 112، دوره 13، شماره 2، مهر 2022، صفحه 1367-1375 اصل مقاله (432.85 K) | ||
| نوع مقاله: Research Paper | ||
| شناسه دیجیتال (DOI): 10.22075/ijnaa.2022.6254 | ||
| نویسندگان | ||
| Jaufar Mousa Mohammed* 1؛ Maysoon M. Aziz2؛ Ammer Fadel Tawfeeq1 | ||
| 1Department statistics, College Administration and Economics, University of Kirkuk, Kirkuk, Iraq | ||
| 2Department Mathematics, College Computer Sciences and Mathematics, University of Mosul, Iraq | ||
| تاریخ دریافت: 10 آذر 1400، تاریخ بازنگری: 27 دی 1400، تاریخ پذیرش: 12 بهمن 1400 | ||
| چکیده | ||
| Introduce some ideas about applied of spatial regression models for independent and dependent fuzzy variables. while the parameters crisp values, which are estimated by the ordinary least squares method. This paper has been formulated fuzzy Pure Spatial Autoregressive Model (FPSAM) from a fuzzy general spatial model, and applied for trapezoidal fuzzy number in the domain traffic accidents for a number of cities in Iraq for the year 2018 and that after converting the Trapezoidal fuzzy number into crisp values by centroid method, calculations the results by Matlab language. | ||
| کلیدواژهها | ||
| fuzzy spatial regression models؛ fuzzy pure spatial autoregressive model؛ centroid method | ||
| مراجع | ||
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[1] A.S. Ahmar and M.K. Aidid, Crime Modeling using Spatial Regression Approach, J. Phys.: Conf. Ser. 954 (2018), no. 1, 012013.[2] Q.N.N. Al-Kazaz and H.J.K. Al-Saadi, Comparing bayes estimation with maximum likelihood estimation of generalized inverted exponential distribution in case of fuzzy data, J. Econ. Admin. Sci. 23 (2017), no. 101. [3] G. Arbia, A primer for spatial econometrics with applications in R, Springer, 2014. [4] B.O. Dalia and F.T. Amer, Estimating parameters of some spatial regression models with experimental and applied study, Department of Statistics, College of Administration and Economics, University of Kirkuk, 2020. [5] M.M. Fischer and J. Wang, Spatial data analysis: models, methods and techniques, Springer Science & Business Media, 2011. [6] M.E. Hassan and A.T. Heba, Fuzzy regression analysis, Iraqi J. Statist. Sci. 10 (2006), 61–84. [7] C. Kao and C.L. Chyu, A fuzzy linear regression model with better explanatory power, Fuzzy Sets Syst. 126 (2002), no. 3, 401–409 [8] K.H. Lee, First course on fuzzy theory and applications, Springer Science & Business Media, 2004. [9] T.J. Ross, Fuzzy logic with engineering applications, John Wiley & Sons, 2005. [10] S.Q. Hadi and O.A.M. Ali, Estimating spatial regression models for poverty rates in the districts of Iraq for the year 2012, Master’s Thesis in Statistics, College of Administration and Economics, University of Baghdad, 2014 [11] E. Tony Smith, Spatial data analysis, School of Engineering and Applied Science, University of Pennsylvania, 2015. [12] Y.J. Wang and H.S. Lee, The revised method of ranking fuzzy numbers with an area between the centroid and original points, Comput. Math. Appl. 55 (2008), no. 9, 2033-2042 [13] Y.M. Wang, J.B. Yang, D.L. Xu and K.S. Chin, On the centroids of fuzzy numbers, Fuzzy Sets Syst. 157 (2006), no. 7, 919–926. [14] A. Zhang, Statistical analysis of fuzzy linear regression model based on centroid method, Appl. Math. 7 (2016), no. 7, 579. | ||
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