Recursive Residuals and Model Diagnostics for Normal and Non-Normal State Space Models

Frühwirth-Schnatter, Sylvia (1994) Recursive Residuals and Model Diagnostics for Normal and Non-Normal State Space Models. Forschungsberichte / Institut für Statistik, 40. Department of Statistics and Mathematics, WU Vienna University of Economics and Business, Vienna.

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Abstract

Model diagnostics for normal and non-normal state space models is based on recursive residuals which are defined from the one-step ahead predictive distribution. Routine calculation of these residuals is discussed in detail. Various tools of diagnostics are suggested to check e.g. for wrong observation distributions and for autocorrelation. The paper also covers such topics as model diagnostics for discrete time series, model diagnostics for generalized linear models, and model discrimination via Bayes factors. (author's abstract)

Item Type: Paper
Keywords: autocorrelation / Bayes factors / generalized linear models / Kalman-filtering / model diagnostics / model discriminat ion / recursive residuals / state space models
Divisions: Departments > Finance, Accounting and Statistics > Statistics and Mathematics
Depositing User: Repository Administrator
Date Deposited: 11 Jul 2006 10:13
Last Modified: 22 Oct 2019 00:41
URI: https://epub.wu.ac.at/id/eprint/1540

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