Fuzzy logistic regression: A new possibilistic model and its application in clinical vague status

Iranian Journal of Fuzzy Systems

Volumn 8, Issue 1, 2011, Pages 1-17

  Pourahmad, S ^a   Ayatollahi, S M T ^a   Taheri, S M ^b  

^a SHIRAZ UNIVERSITY OF MEDICAL SCIENCES   (Iran)

^b ISFAHAN UNIVERSITY OF TECHNOLOGY   (Iran)

Author keywords

Clinical research; Fuzzy logistic regression; Logistic regression; Possibilistic odds

Indexed keywords

EID: 79955003085     PISSN: 17350654     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (26)

1. Agresti, Categorical data analysis, Wiley, New york, 2002.
2. A. R. Arabpour and M. Tata, Estimating the parameters of a fuzzy linear regression model, Iranian Journal ofFuzzy Systems, 5 (2008), 1-19.
3. S. C. Bagley, H. White and B. A. Golomb, Logistic regression in the medical literature: standards for use and reporting with particular attention to one medical domain, Journal of Clinical Epidemiology, 54 (2001), 979-985.
4. Celmins, Least squares model fitting to fuzzy vector data, Fuzzy Sets and Systems, 22 (1987), 260-269.
5. R. Coppi, P. D'Urso, P. Giordani and A. Santoro, Least squares estimation of a linear regression model with LR fuzzy response, Computational Statistics and Data Analysis, 51 (2006), 267-286.
6. P. Diamond, Least squares fitting of several fuzzy variables, Proc. ofthe Second IFSA Congress, Tokyo, (1987), 20-25.
7. D. Dubois, E. Kerre, R. Mesiar and H. Prade, Fuzzy interval analysis, In: D. Dubois, H. Prade, eds., Fundamentals ofFuzzy Sets, Kluwer, 2000.
8. A. S. Fauci, E. Braunwald, D. L. Kasper, S. L. Hauser, D. L. Longo, J. L. Jameson and J. Loscalzo, Harrison's principals of internal medicine, Wiley, New York, II (2008), 2275-2279.
9. GAMS (General Algebraic Modeling System), A high-level modeling system for mathematical programming and optimization, GAMS Development Corporation, Washington, DC, USA, 2007.
10. H. Hassanpour, H. R. Maleki and M. A. Yaghoobi, A note on evaluation of fuzzy linear regression models by comparing membership functions, Iranian Journal ofFuzzy Systems, 6 (2009), 1-6.
11. D. H. Hong, J. Song and H. Y. Do, Fuzzy least-squares linear regression analysis using shape preserving operation, Information Sciences, 138 (2001), 185-193.
12. LINGO 8.0, A linear programming, integer programming, nonlinear programming and global optimization solver, Lindo System Inc, 1415 North Dayton Str., Chicago, 2003.
13. MATLAB R., A technical computing environment for high-performance numeric computation and Visualization, The Math Works Inc., 2007.
14. S. Mirzaei Yeganeh and S. M. Taheri, Possibilistic logistic regression by linear programming approach, Proc. oft he 7th Seminar on Probability and Stochastic Processes, Isfahan University ofT echnology, Isfahan, Iran, (2009), 139-143.
15. J. Mohammadi and S. M. Taheri, Pedomodels fitting with fuzzy least squares regression, Iranian Journal ofFuzzy Systems, 1 (2004), 45-61.
16. Peters, A linear forecasting model and its application in economic data, Journal ofF orecasting, 20 (2001), 315-328.
17. S. Roychowdhury and W. Pedrycz, Modeling temporal functions with granular regression and fuzzy rule, Fuzzy Sets and Systems, 126 (2002), 377-387.
18. B. Sadeghpour and D. Gien, A goodness of fit index to reliability analysis in fuzzy model, In: A. Grmela, ed., Advances in Intelligent Systems, Fuzzy Systems, Evolutionary Computation, WSEAS Press, Greece, (2002), 78-83.
19. A. F. Shapiro, Fuzzy regression models, ARC, 2005.
20. B. D. Tabaei, and W. H. Herman, A multivariate logistic regression equation to screen for Diabetes, Diabetes Care, 25 (2002), 1999-2003.
21. Taheri, Trends in fuzzy statistics, Austrian Journal of Statistics, 32 (2003), 239-257.
22. S. M. Taheri and M. Kelkinnama, Fuzzy least absolutes regression, Proc. of4th International IEEE Conference on Intelligent Systems, Varna, Bulgaria, 11 (2008), 55-58.
23. H. Tanaka, S. Uejima, K. Asai, Linear regression analysis with fuzzy model, IEEE Trans. Systems Man Cybernet., 12 (1982), 903-907.
24. E. Van Broekhoven and B. D. Baets, Fast and accurate of gravity defuzzification of fuzzy systems outputs defined on trapezoidsal fuzzy partitions, Fuzzy Sets and Systems, 157 (2006), 904-918.
25. Zadeh, Fuzzy sets, Information and Control, 8 (1965), 338-353.
26. H. J. Zimmermann, Fuzzy set theory and its applications, 3rd ed., Kluwer, Dodrecht, 1996.