Resource title

Integration-based Kalman-filtering for a Dynamic Generalized Linear Trend Model

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The topic of the paper is filtering for non-Gaussian dynamic (state space) models by approximate computation of posterior moments using numerical integration. A Gauss-Hermite procedure is implemented based on the approximate posterior mode estimator and curvature recently proposed in 121. This integration-based filtering method will be illustrated by a dynamic trend model for non-Gaussian time series. Comparision of the proposed method with other approximations ([15], [2]) is carried out by simulation experiments for time series from Poisson, exponential and Gamma distributions. (author's abstract) ; Series: Forschungsberichte / Institut für Statistik

Resource author

Sylvia Schnatter

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Resource language

en

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application/pdf

Resource resource URL

http://epub.wu.ac.at/424/1/document.pdf

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