Hostname: page-component-848d4c4894-hfldf Total loading time: 0 Render date: 2024-06-01T14:59:15.728Z Has data issue: false hasContentIssue false

On a generalization of the ehrenfest urn model

Published online by Cambridge University Press:  14 July 2016

Holger Dette*
Affiliation:
Technische Universität Dresden
*
Postal address: Institut für Mathematische Stochastik, Abteilung Mathematik, Technische Universität Dresden, Mommsenstr. 13, 01062 Dresden, Germany.

Abstract

Krafft and Schaefer [14] considered a two-parameter Ehrenfest urn model and found the n-step transition probabilities using representations by Krawtchouk polynomials. For a special case of the model Palacios [17] calculated some of the expected first-passage times. This note investigates a generalization of the two-parameter Ehrenfest urn model where the transition probabilities pi,i+1 and pi,i+1 are allowed to be quadratic functions of the current state i. The approach used in this paper is based on the integral representations of Karlin and McGregor [9] and can also be used for Markov chains with an infinite state space.

Type
Research Article
Copyright
Copyright © Applied Probability Trust 1994 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Footnotes

Research supported in part by the Deutsche Forschungsgemeinschaft.

References

[1] Abramowitz, M. and Stegun, I. A. (1964) Handbook of Mathematical Functions , 9th edn. Dover, New York.Google Scholar
[2] Askey, R. (1975) Orthogonal Polynomials and Special Functions. SIAM, Philadelphia, PA.Google Scholar
[3] Bailey, N. T. (1984) The Elements of Stochastic Processes. Wiley, New York.Google Scholar
[4] Bingham, N. H. (1991) Fluctuation theory for the Ehrenfest urn. Adv. Appl. Prob. 23, 598611.Google Scholar
[5] Chihara, T. S. (1978) An Introduction to Orthogonal Polynomials. Gordon and Breach, New York.Google Scholar
[6] Dette, H. (1990) A generalization of D- and D1-optimal designs in polynomial regression. Ann. Statist. 18, 17841804.Google Scholar
[7] Gasper, G. (1975) Positivity and special functions. In Theory and Applications of Special Functions , ed. Askey, R., pp. 375433. Academic Press, New York.Google Scholar
[8] Ismail, M. E. H., Letessier, J. and Valent, G. (1989) Quadratic birth and death processes and associated continuous dual Hahn polynomials. SIAM J. Math. Anal. 20, 727737.Google Scholar
[9] Karlin, S. and Mcgregor, J. (1959) Random walks. Illinois J. Math. 3, 6681.Google Scholar
[10] Karlin, S. and Mcgregor, J. (1959) A characterization of birth and death processes. Proc. Nat. Acad. Sci. U.S.A. 45, 375379.Google Scholar
[11] Karlin, S. and Mcgregor, J. (1961) The Hahn polynomials, formulas and an application. Scripta Math. 26, 3346.Google Scholar
[12] Karlin, S. and Mcgregor, J. (1965) Ehrenfest urn models. J. Appl. Prob. 2, 352376.CrossRefGoogle Scholar
[13] Kendall, D. G. (1958) Integral representations for Markov transition probabilities. Bull. Amer. Math. Soc. 64, 358362.Google Scholar
[14] Krafft, O. and Schaefer, M. (1993) Mean passage times for triangular transition matrices and a two parameter Ehrenfest urn model. J. Appl. Prob. 30, 964970.Google Scholar
[15] Letessier, J. and Valent, G. (1984) The generating function method for quadratic asymptotically symmetric birth and death processes. SIAM J. Appl. Math. 44, 773783.Google Scholar
[16] Moran, P. A. P. (1958) Random processes in genetics. Proc. Camb. Phil. Soc. 54, 6072.Google Scholar
[17] Palacios, J. L. (1993) Fluctuation theory for the Ehrenfest urn via electronic networks. Adv. Appl. Prob. 25, 472476.Google Scholar
[18] Rahman, M. (1978) A positive kernel for Hahn Eberlein polynomials. SIAM J. Math. 9, 891905.Google Scholar
[19] Roehmer, B. and Valent, G. (1982) Solving the birth and death processes with quadratic asymptotically symmetric transition rates. SIAM J. Appl. Math. 42, 10201046.Google Scholar
[20] Skibinsky, M. (1968) Extreme nth moments on [0, 1] and the inverse of a moment space map. J. Appl. Prob. 5, 693701.Google Scholar
[21] Skibinsky, M. (1986) Principal representations and canonical moment sequences for distributions on an interval. J. Math. Anal. Appl. 120, 95120.Google Scholar
[22] Sloane, N. J. A. (1975) An introduction to association schemes and coding theory. In Theory and Application of Special Functions , ed. Askey, R., pp. 225260. Academic Press, New York.Google Scholar
[23] Stanton, D. (1984) Orthogonal polynomials and Chevalley groups. In Special Functions: Group Theoretical Aspects and Applications , ed. Askey, R., Koornwinder, T. H. and Schempp, W., pp. 87127. Reidel, Dordrecht.Google Scholar
[24] Szegö, G. (1975) Orthogonal Polynomials. Amer. Math. Soc. Colloq. Publ. 23, American Mathematical Society, Providence, RI.Google Scholar