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

Sylvia Schnatter

Publikation: Working/Discussion PaperWU Working Paper

Abstract

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)
OriginalspracheEnglisch
ErscheinungsortVienna
HerausgeberDepartment of Statistics and Mathematics, WU Vienna University of Economics and Business
PublikationsstatusVeröffentlicht - 1991

Publikationsreihe

NameForschungsberichte / Institut für Statistik
Nr.9

WU Working Paper Reihe

  • Forschungsberichte / Institut für Statistik

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