Athreya, K. B. and Karlin, S. (1968). Embedding of urn schemes into continuous time Markov branching processes and related limit theorems. Ann. Math. Statist.
Bai, Z. and Hu, F. (1999). Asymptotic theorems for urn models with nonhomogeneous generating matrices. Stoch. Process. Appl.
Bai, Z. and Hu, F. (2005). Asymptotics in randomized urn models. Ann. Appl. Prob.
Bai, Z., Hu, F. and Zhang, L.-X. (2002). Gaussian approximation theorems for urn models and their applications. Ann. Appl. Prob.
Balaji, S., Mahmoud, H. and Watanabe, O. (2006). Distributions in the Ehrenfest process. Statist. Prob. Lett.
Baldi Antognini, A. (2005). On the speed of convergence of some urn designs for the balanced allocation of two treatments. Metrika
Brémaud, P. (1999). Markov chains. Gibbs fields, Monte Carlo simulation, and Queues (Texts Appl. Math. 31). Springer, New York.
Chan, K. and Geyer, C. (1994). Discussion: Markov chains for exploring posterior distributions. Ann. Statist.
Chen, Y.-P. (2000). Which design is better? Ehrenfest urn versus biased coin. Adv. Appl. Prob.
Chen, Y.-P. (2006). A central limit property under a modified Ehrenfest urn design. J. Appl. Prob.
Dette, H. (1994). On a generalization of the Ehrenfest urn model. J. Appl. Prob.
Flajolet, P., Gabarró, J. and Pekari, H. (2005). Analytic urns. Ann. Prob.
Garibaldi, U. and Penco, M. (2000). Ehrenfest's urn model generalized: an exact approach for market participation models. Statistica Applicata
Gouet, R. (1993). Martingale functional central limit theorems for a generalized Pólya urn. Ann. Prob.
Hall, P. and Heyde, C. C. (1980). Martingale Limit Theory and Its Application. Academic Press, New York.
Higueras, I., Moler, J., Plo, F. and San Miguel, M. (2003). Urn models and differential algebraic equations. J. Appl. Prob.
Higueras, I., Moler, J., Plo, F. and San Miguel, M. (2006). Central limit theorems for generalized Pólya urn models. J. Appl. Prob.
Hu, F. and Rosenberger, W. (2003). Optimality, variability, power: evaluating response-adaptive randomization procedures for treatment comparisons. J. Amer. Statist. Assoc.
Janson, S. (2004). Functional limit theorems for multitype branching processes and generalized Pólya urns. Stoch. Process. Appl.
Johnson, N. L. and Kotz, S. (1977). Urn Models and Their Application. John Wiley, New York.
Krafft, O. and Schaefer, M. (1993). Mean passage times for tridiagonal transition matrices and a two-parameter Ehrenfest urn model. J. Appl. Prob.
Muliere, P., Paganoni, A. and Secchi, P. (2006). A randomly reinforced urn. J. Statist. Planning Infer. 136, 1853–1874.
Rosenberger, W. (2002). Randomized urn models and sequential designs. Sequential Anal. 21, 1–28.
Schouten, H. (1995). Adaptive biased urn randomization in small strata when blinding is impossible. Biometrics
Smythe, R. T. (1996). Central limit theorems for urn models. Stoch. Process. Appl.
Wei, L. (1977). A class of designs for sequential clinical trials. J. Amer. Statist. Assoc.
Wei, L. (1978). An application of an urn model to the design of sequential controlled clinical trials. J. Amer. Statist. Assoc.
Wei, L. (1979). The generalized Pólya's urn design for sequential medical trials. Ann. Statist.
Zhang, L.-X., Hu, F. and Cheung, S. H. (2006). Asymptotic theorems of sequential estimation-adjusted urn models. Ann. Appl. Prob.