A Kalman filter for a Poisson series with covariates and Laplace approximation integration
By: Donald P. Gaver, Patricia A. Jacobs
Contributors: Jacobs, Patricia A.; Naval Postgraduate School (U.S.). Dept. of Operations Research
Publisher: Naval Postgraduate School; Available from National Technical Information Service
Published: 1991
Place of publication: Monterey, Calif; Springfield, Va
Language: eng
Number of pages: 44
Subjects: Time series analysis; Kalman filtering; Mathematical prediction; Approximation(Mathematics)
Other titles: NPS-OR-91-030.
Description: A hierarchical model for a Poisson time series is introduced. The model allows the mean or      rate of the Poisson variables to vary slowly in time; it is modeled as the exponential of an      AR/1 process. In addition the rate is influenced by a covariate. The Laplace method is used to      recursively update some model parameter estimates. Frankly heuristic methods are explored      to estimate other of the underlying parameters. The methodology is checked against simulated      data with encouraging results.
Notes: Title from cover.

"NPS-OR-91-030."

"September 1991."

AD A242 960.

Includes bibliographical references (p. 36-37)

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