Convergence and the constant dynamic linear model
UNSPECIFIED (1997) Convergence and the constant dynamic linear model. JOURNAL OF FORECASTING, 16 (5). pp. 287-292. ISSN 0277-6693Full text not available from this repository.
It is well known that, as calculated using the Kalman filter 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 specific 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. (C) 1997 John Wiley & Sons, Ltd.
|Item Type:||Journal Article|
|Subjects:||H Social Sciences > HD Industries. Land use. Labor > HD28 Management. Industrial Management
H Social Sciences > HD Industries. Land use. Labor
|Journal or Publication Title:||JOURNAL OF FORECASTING|
|Publisher:||JOHN WILEY & SONS LTD|
|Number of Pages:||6|
|Page Range:||pp. 287-292|
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