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Claim reserving with fuzzy regression

Year 2015, Volume: 36 Issue: 3, 704 - 709, 13.05.2015

Tahereh Bahramı , Masuod Bahramı

Abstract

Abstract. Claims reserving plays a key role for the insurance. Therefore, various statistical methods are used to provide for an adequate amount of claim reserves. Since claim reserves are always variable, fuzzy set theory is used to handle this variability. In this paper, non-symmetric fuzzy regression is integrated in the Taylor’s method to develop a new method for claim reserving.

Keywords

Fuzzy number fuzzy regression claim reserves Taylor’s geometric separation method

References

  • Chang, P.T., Lee, E.S., 1996. A generalization fuzzy weighted least-squares regression.
  • Fuzzy Sets systems 82, 289-298. Chang, P.T., 1997. Fuzzy seasonality forecasting. Fuzzy Sets Systems 90, 1-10.
  • Diamond, P., Kloeden, P. 1994. Metric Spaces of Fuzzy Sets. Theory and Application.
  • World Scientific, Singapore. Dubois, D., Prade, H., 1980. Fuzzy Sets and Systems: Theory and Applications. Academic Press, New York.
  • Kacprzyk, J., Fedrizzi, M, (Eds.), 1992.Fuzzy regression Analysis. Omnitech and Heidelbreg: Physic, Waesaw.
  • Tanaka, H., S. Uejima and K. Asai. 1982. Liner regression analysis with Fuzzy model.
  • IEEE Trans. System Man Cybernet. 12: 903-907. Zimmermann, H. J. 1996. Fuzzy Sets Theory and Its application. Kluwer Academic Pub. , Boston. )n n ∑ ∑ =i 1j=−+i+i+1 =i 1j=−+i+i+1 =i n+i+1 n n+i+1 n+i+1 rˆCji ,Cjiji 2 2i1j=−+i+i+11

Year 2015, Volume: 36 Issue: 3, 704 - 709, 13.05.2015

Tahereh Bahramı , Masuod Bahramı

Abstract

References

  • Chang, P.T., Lee, E.S., 1996. A generalization fuzzy weighted least-squares regression.
  • Fuzzy Sets systems 82, 289-298. Chang, P.T., 1997. Fuzzy seasonality forecasting. Fuzzy Sets Systems 90, 1-10.
  • Diamond, P., Kloeden, P. 1994. Metric Spaces of Fuzzy Sets. Theory and Application.
  • World Scientific, Singapore. Dubois, D., Prade, H., 1980. Fuzzy Sets and Systems: Theory and Applications. Academic Press, New York.
  • Kacprzyk, J., Fedrizzi, M, (Eds.), 1992.Fuzzy regression Analysis. Omnitech and Heidelbreg: Physic, Waesaw.
  • Tanaka, H., S. Uejima and K. Asai. 1982. Liner regression analysis with Fuzzy model.
  • IEEE Trans. System Man Cybernet. 12: 903-907. Zimmermann, H. J. 1996. Fuzzy Sets Theory and Its application. Kluwer Academic Pub. , Boston. )n n ∑ ∑ =i 1j=−+i+i+1 =i 1j=−+i+i+1 =i n+i+1 n n+i+1 n+i+1 rˆCji ,Cjiji 2 2i1j=−+i+i+11
There are 7 citations in total.

Details

Journal Section Special
Authors

Tahereh Bahramı

Masuod Bahramı This is me

Publication Date May 13, 2015
Published in Issue Year 2015 Volume: 36 Issue: 3

Cite

APA Bahramı, T., & Bahramı, M. (2015). Claim reserving with fuzzy regression. Cumhuriyet Üniversitesi Fen Edebiyat Fakültesi Fen Bilimleri Dergisi, 36(3), 704-709.
AMA Bahramı T, Bahramı M. Claim reserving with fuzzy regression. Cumhuriyet Üniversitesi Fen Edebiyat Fakültesi Fen Bilimleri Dergisi. May 2015;36(3):704-709.
Chicago Bahramı, Tahereh, and Masuod Bahramı. “Claim Reserving With Fuzzy Regression”. Cumhuriyet Üniversitesi Fen Edebiyat Fakültesi Fen Bilimleri Dergisi 36, no. 3 (May 2015): 704-9.
EndNote Bahramı T, Bahramı M (May 1, 2015) Claim reserving with fuzzy regression. Cumhuriyet Üniversitesi Fen Edebiyat Fakültesi Fen Bilimleri Dergisi 36 3 704–709.
IEEE T. Bahramı and M. Bahramı, “Claim reserving with fuzzy regression”, Cumhuriyet Üniversitesi Fen Edebiyat Fakültesi Fen Bilimleri Dergisi, vol. 36, no. 3, pp. 704–709, 2015.
ISNAD Bahramı, Tahereh - Bahramı, Masuod. “Claim Reserving With Fuzzy Regression”. Cumhuriyet Üniversitesi Fen Edebiyat Fakültesi Fen Bilimleri Dergisi 36/3 (May 2015), 704-709.
JAMA Bahramı T, Bahramı M. Claim reserving with fuzzy regression. Cumhuriyet Üniversitesi Fen Edebiyat Fakültesi Fen Bilimleri Dergisi. 2015;36:704–709.
MLA Bahramı, Tahereh and Masuod Bahramı. “Claim Reserving With Fuzzy Regression”. Cumhuriyet Üniversitesi Fen Edebiyat Fakültesi Fen Bilimleri Dergisi, vol. 36, no. 3, 2015, pp. 704-9.
Vancouver Bahramı T, Bahramı M. Claim reserving with fuzzy regression. Cumhuriyet Üniversitesi Fen Edebiyat Fakültesi Fen Bilimleri Dergisi. 2015;36(3):704-9.