摘要: This chapter deals with likelihood-based inference for ergodic finite as well infinite Markov chains. We also consider extensions of chain models, such Hidden chain, chains based on polytomous regression, and Raftery’s Mixture Transition Density model. These models have less number parameters compared to a higher order chain. Lastly, we discuss methods estimation in grouped data from
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