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Convergence and the Constant Dynamic Linear Model

โœ Scribed by P. J. Harrison

Publisher
John Wiley and Sons
Year
1997
Tongue
English
Weight
121 KB
Volume
16
Category
Article
ISSN
0277-6693

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โœฆ Synopsis

It is well known that, as calculated using the Kalman ยฎlter recurrence relationships, the posterior parameter variance and the adaptive vector of observable constant dynamic linear models converge to limiting values. However, most proofs are tortuous, some have subtle errors and some relate only to speciยฎc cases. An elegant probabilistic convergence proof demonstrates that the limit is independent of the initial parametric prior. The result is extended to a class of multivariate dynamic linear models. Finally the proof is shown to apply to many non-observable constant DLMs.

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