Higher-order hidden markov models with applications to DNA sequences

Hidden Markov models (HMMs) have been applied to many real-world applications. Very often HMMs only deal with the first order transition probability distribution among the hidden states. In this paper we develop higher-order HMMs. We study the evaluation of the probability of a sequence of observations based on higher-order HMMs and determination of a best sequence of model states. © Springer-Verlag 2003.link_to_subscribed_fulltex