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具有随机进入与退出的马尔可夫链推断AI 解读

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…

具有随机进入与退出机制的马尔可夫链推断AI 解读

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…