1 منابع

منابع

[1] Asadi, M., Ebrahimi, N., Hamedani, G.G., Soofi, E.S., 2004. Maximum dynamic entropy models. IEEE Trans. Inform. Theory 50,177–183.

[2]Chan, L.K.(1967) On a characterization of distributions by expected values of extreme order statistics. Am. Math. Mthly, 74, 950-951

[3]David, H. A. (1981) Order Statistics, 2nd edn. New York: Wiley

[4] Ebrahimi, N., 2000. The maximum entropy method for lifetime distributions. Sankhy¯ A 62, 236–243.a

[5] Elamir, E.A.H., Seheult, A.H., 2004. Exact variance structure of sample L-moments. J. Statist. Plann. Inference 124, 337–359.

[6] Goel, N.K., Burn, D.H., Pandey, M.D., An, Y., 2004. Wind quantile estimation using a pooled frequency analysis approach. J. Wind Eng. Indust. Aerodynam. 92, 509–528.

[7] Holm, J., 1993. Maximum entropy Lorenz curves. J. Econometrics 59, 377–389.

[8] Hosking, J.R.M., 1990. L-moments: analysis and estimation of distributions using linear combinations of order statistics. J. Roy. Statist. Soc. B 52, 105–124.

[9]Hosking, J.R.M., 1996. Fortran routines for use with the method of L-moments, version 3. Research Report RC20525, IBM Research Division,

Yorktown Heights, NY.

[10] Ihara, 1993. Information Theory for continues systems

[11]Hosking, J.R.M., 1998. L-moments. In: Kotz, S., Read, C., Banks, D.L. (Eds.), Encyclopedia of Statistical Sciences, vol. 2. Wiley, New York,

pp. 357–362.

[12] Dembo, TM cover,1991. Information theoretic inequality. JA Thomas Information theory , IEEE Transactions on,

[13] Hosking, J.R.M., 2006. Supplement to “Distributions with maximum entropy subject to constraints on their L-moments”. Research Report RC24177, IBM Research Division, Yorktown Heights, NY.

[14] Jaynes, E.T., 1957. Information theory and statistical mechanics. Phys. Rev. 106, 620–630.

[15] Johnson, N.L., Kotz, S., Balakrishnan, N., 1995. Continuous Univariate Distributions, second ed., vol. 2, Wiley, New York.

[16] Jones, M.C., Balakrishnan, N., 2002. How are moments and moments of spacings related to distribution functions? J. Statist. Plann. Inference 103,

377–390.

[17] Kapur, J.N., 1994. Measures of Information and their Applications. Wiley, New York.

[18] Karvanen, J., Eriksson, J., Koivunen, V., 2002. Adaptive score functions for maximum likelihood ICA. J. VLSI Sig. Proc. 32, 83–92.

[19] Kjeldsen, T.R., Smithers, J.C., Schulze, R.E., 2002. Regional flood frequency analysis in the KwaZulu-Natal province, South Africa, using theindex-flood method. J. Hydrol. 255, 194–211.

[20]Konheim, A. G. (1971) A note on order statistics . Am. Math. Mathly , 78, 524.

[21] Kroll, C.N., Vogel, R.M., 2002. Probability distribution of low streamflow series in the United States. J. Hydrol. Eng. 7, 137–146.

[22] Landwehr JM, MatalasNC, Wallis JR (1979) Probability-weighted moments compared with some traditional techniques in estimating Gumbel parameters and quantiles. Water Resour. Res. 15, 1055-1064

[23] Pandey, M.D., 2000. Direct estimation of quantile functions using the maximum entropy principle. Struct. Safety 22, 61–79.

[24] Parzen, E., 1979. Nonparametric statistical data modeling. J. Amer. Statist. Assoc. 74, 105–121.

[25] Rényi, A., 1961. On measures of entropy and information. In: Proceedings of the Fourth Berkeley Symposium on Mathematical Statistics andProbability.University of California Press, Berkeley, CA, pp. 547–561.

[26] Rietsch E (1977) The maximum entropy approach to inverse problem. J. Geophysics 42, 489-506

[27] Sansone, G., 1959. Orthogonal Functions. Interscience Publishers, New York.

[28] Sacchi MD (1996) Aperture compensated Radon and Fourier transforms, Ph.D. thesis, UBC, Vancouver, Canada

[29] Silverman, B.W., 1986. Density Estimation for Statistics and Data Analysis. Chapman & Hall, London.

[30] Soofi, E.S., 1994. Capturing the intangible concept of information. J. Amer. Statist. Assoc. 89, 1243–1254.

[31] Shannon CE (1948) A mathematical theory of communication. Bell Systems Technical J. 27, 379-423

[32] Thomas M.Cover, Joy A. Thomas, 1991.Elements of Information Theory.A wiley-Interscience publication.

[33] Troutman, J.L., 1983. Variational Calculus with Elementary Convexity. Springer, Berlin.

[34] Ulrych, T.J., Velis, D.R., Woodbury, A.D., Sacchi, M.D., 2000. L-moments and C-moments. Stoch. Envir. Res. Risk Assess. 14, 50–68.

[35] Ulrych TJ (1998) The ``whiteness'' hypothesis: re¯ectivity, inversion, chaos and Enders. submitted to Geophysics

[36] Wand, M.P., Jones, M.C., 1995. Kernel Smoothing. Chapman & Hall, London.

[37] Wang QJ (1996) Direct sample estimators of L moments. Water Resour. Res. 32, 3617-3619

[38] Woodbury AD (1989) Bayesian updating revisited. Math. Geology 21(3), 285-308

[39] Yue, S., Pilon, P., 2005. Probability distribution type of Canadian annual minimum streamflow. Hydrol. Sci. J. 50, 427–438.

[40] Zaidman, M.D., Keller, V., Young, A.R., Cadman, D., 2003. Flow-duration-frequency behaviour of British rivers based on annual minima data. J.ydrol. 277, 195–213.

]41[پایان نامه کارشناسی ارشد "آنتروپی گذشته تعمیم یافته" 1386، مسعود کلهر، استاد راهنما:دکتر عین اله پاشا.

]2[4پایان نامه کارشناسی ارشد "ویژگی مقعر لوگی و ماکزیمم آنتروپی توزیع پواسون " 1386، احسان قاسمی، استاد راهنما:دکتر علی اکبر رحیم زاده.