Quotation Frühwirth-Schnatter, Sylvia. 1994. Data augmentation and dynamic linear models. Journal of Time Series Analysis. 15 183-202.


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Abstract

We define a subclass of dynamic linear models with unknown hyperparameters called d-inverse-gamma models. We then approximate the marginal p.d.f.s of the hyperparameter and the state vector by the data augmentation algorithm of Tanner/Wong. We prove that the regularity conditions for convergence hold. A sampling based scheme for practical implementation is discussed. Finally, we illustrate how to obtain an iterative importance sampling estimate of the model likelihood.

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Publication's profile

Status of publication Published
Affiliation WU
Type of publication Journal article
Journal Journal of Time Series Analysis
Citation Index SCI
WU-Journal-Rating new FIN-A, VW-D, WH-B
Language English
Title Data augmentation and dynamic linear models
Volume 15
Year 1994
Page from 183
Page to 202
URL http://epub.wu.ac.at/392/1/document.pdf
DOI http://dx.doi.org/10.1111/j.1467-9892.1994.tb00184.x
Open Access N

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Frühwirth-Schnatter, Sylvia (Details)
Organization
Institute for Statistics and Mathematics IN (Details)
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