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- W2963246451 abstract "We develop a recursion for hidden Markov model of any order h, which allows us to obtain the posterior distribution of the latent state at every occasion, given the previous h states and the observed data. With respect to the well-known Baum-Welch recursions, the proposed recursion has the advantage of being more direct to use and, in particular, of not requiring dummy renormalizations to avoid numerical problems. We also show how this recursion may be expressed in matrix notation, so as to allow for an efficient implementation, and how it may be used to obtain themanifest distribution of the observed data and for parameter estimation within the Expectation-Maximization algorithm. The approach is illustrated by an applicationto nancial data which is focused on the study of the dynamics of the volatility level of log-returns." @default.
- W2963246451 created "2019-07-30" @default.
- W2963246451 creator A5054448743 @default.
- W2963246451 date "2011-12-31" @default.
- W2963246451 modified "2023-09-27" @default.
- W2963246451 title "An alternative to the Baum-Welch recursions for hidden Markov models" @default.
- W2963246451 hasPublicationYear "2011" @default.
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