Seasonal Hidden Markov Models for Stochastic Time Series with Periodically Varying Characteristics

Seasonal Hidden Markov Models for Stochastic Time Series with Periodically Varying Characteristics

Novel seasonal hidden Markov models (SHMMs) for stochastic time series with periodically varying characteristics are developed. Nonlinear interactions among SHMM parameters prevent the use of the forward-backward algorithms which are usually used to fit hidden Markov models to a data sequence. Inste...

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Bibliographic Details
Main Author: Lewis, Arthur M.
Format: Others
Published: PDXScholar 1995
Subjects:
Markov processes > Computer programs
Precipitation variability > Computer programs
Electrical and Computer Engineering
Electrical and Electronics
Online Access:https://pdxscholar.library.pdx.edu/open_access_etds/5056
https://pdxscholar.library.pdx.edu/cgi/viewcontent.cgi?article=6128&context=open_access_etds

Internet

https://pdxscholar.library.pdx.edu/open_access_etds/5056
https://pdxscholar.library.pdx.edu/cgi/viewcontent.cgi?article=6128&context=open_access_etds

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