| Reference: | 參考文獻
一、中文部分
1.張金裕，臺灣保險事業之風險模型與風撿管理，國立中興大學統計系，民國七十八年。
2.張金裕，保險事業之運轉模型與其風險管理，國立中興大學統計系，民國七十九年。
3.行政院主計處編，中華民國臺灣地區物價統計月報，民國七十八年一月。
4. 臺北市人壽保險商業同業公會編，人壽保險業務統計年報，民國六十三年至七十八年。
二、英文部分
1. Berliner, Barch (1982). Limits of Insurability of Risk. Englewood Cliffs, New Jersey: Prentice Hall Inc.
2. Beard, R. E. , Pentikainen, T. and Pesonen, E. ( 1984). Risk Theory: The Stochastic Basis of Insurance. Cambridge: University Printing House.
3. Bhat, U. N. (1972). Elements of Applied Stochastic Processes. New York:John Wiley & Sons Inc.
4. Bowers, N. L. (1966). "Expansions of Probability Density Functions as a Sum of Gamma Densities with Applications in Risk Theory." Transactions of the Society of Actuaries, X VIII, pp. 295-309.
5. Bowers, N. L. Gerber, H. U. , Hickman, J. C., Jones, D. A. and Nesbitt, C.J. (1986). Risk Theory: to be included in a textbook entitled:Actuarial Mathematics.中華民國精算學會。
6. Box, G. E. P. and Jenkins, G. M. (1976). Time Series Analysis:Forecasting and Control. San Francisco: Holden - Day Inc.
7. Gerber, H. U. (1979). An Introduction to Mathematical Risk Theory.Huebner Foundation Monographs, Homewood, Ill. : Richard D. Irwin Inc.
8. Kauppi, L. and Ojantakanen, P. (1969). "Approximations of the Generalized Poisson Functions." ASTIN Bulletin, V.
9. Lundberg, O. (1964). On Random Processes and Their Application to Siclcness and Accident Statistics, (reprint of thesis 1940). Uppsala :Almqvist and Wiksells.
10. Panjer, H. H. (1980). "The Aggregate Claim Distribution and Stop-Loss Reinsurance." Transactions of the Society of Actuaries,X X X II , pp.523-535.
11. Pesonen, E. ( 1967). /I On the Calculation of the Generalized Poisson Function." ASTIN Bulletin, N, pp.120-128.
12. Ross, S. (1985). Introduction to Probability Models. London: Academic Press.
13. Seal, H. L. (1978). "From Aggregate Claim Distribution to Probability of Ruin." ASTIN Bulletin, X, pp. 47- 53.
14. Seal,H. L. (1978). Survival Probabilities-The Goal of Risk Theory.New York: John Wiley &. Sons Inc.
15. Vandaele, W. (1983). Applied Time Series and Box-Jenkins Models. New York: Academic Press. |
