- Bayesian latent Markov models

In this chapter1, we consider Bayesian estimation of latent Markov (LM) models as an alternative to maximum likelihood estimation. In the Bayesian framework, specifying appropriate prior distributions on the parameters, which are now random variables, is necessary and also permits the incorporation of prior belief into the model. The posterior distribution of the parameters, which is proportional to the likelihood multiplied by the prior density, is then used for inference on these parameters.