Multi-state Markov processes have been introduced recently in Health Sciences in order to study disease history events. This sort of model have some advantages respect to traditional survival analysis, therefore they are an important line of research into stochastic processes applied to Epidemiology. However these types of models increase the complexity of analysis, even for simpler processes, and standard software is limited. In this paper, two methods for fitting homogeneous Markov models are proposed and compared
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