Abstract
Notions of Bayesian analysis are reviewed, with emphasis on Bayesian modeling and Bayesian calculation. A general hierarchical model for time series analysis is then presented and discussed. Both discrete time and continuous time formulations are discussed. An brief overview of generalizations of the fundamental hierarchical time series model concludes the article.
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© 1996 Springer Science+Business Media Dordrecht
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Berliner, L.M. (1996). Hierarchical Bayesian Time Series Models. In: Hanson, K.M., Silver, R.N. (eds) Maximum Entropy and Bayesian Methods. Fundamental Theories of Physics, vol 79. Springer, Dordrecht. https://doi.org/10.1007/978-94-011-5430-7_3
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DOI: https://doi.org/10.1007/978-94-011-5430-7_3
Publisher Name: Springer, Dordrecht
Print ISBN: 978-94-010-6284-8
Online ISBN: 978-94-011-5430-7
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