Inference for Markov Chains Having Stochastic Entry and Exit
Abstract Models suitable for statistical inference in Markov chains are considered featuring various forms of stochastic entry, including Poisson, renewable binomial pool, uncertain pool size, negative binomial, and input-output reservoir. A parallel inactive states model is suggested for exit. Maximum likelihood estimates are obtained and likelihood ratio tests derived. An application is made to the distribution of Ninth Federal Reserve District member banks with respect to the ratio of farm loans to total loans.