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 fĂĽr Statistik
Identifer | oai:union.ndltd.org:VIENNA/oai:epub.wu-wien.ac.at:epub-wu-01_a06 |
Date | January 1991 |
Creators | Schnatter, Sylvia |
Publisher | Department of Statistics and Mathematics, WU Vienna University of Economics and Business |
Source Sets | Wirtschaftsuniversität Wien |
Language | English |
Detected Language | English |
Type | Paper, NonPeerReviewed |
Format | application/pdf |
Relation | http://epub.wu.ac.at/424/ |
Page generated in 0.2459 seconds