Statistical models called hidden Markov models are a recurring theme in computational biology. What are hidden Markov models, and why are they so useful for so many different problems?

Hidden Markov models (HMMs) are a formal foundation for making probabilistic models of linear sequence 'labeling' problems 1,2. They provide a conceptual toolkit for building complex models just by ...

This is a preview. Log in through your library . Abstract Hidden Markov models (HMMs) are flexible time series models in which the distribution of the observations depends on unobserved serially ...

We consider penalized estimation in hidden Markov models (HMMs) with multivariate Normal observations. In the moderate-to-large dimensional setting, estimation for HMMs remains challenging in practice ...