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Bayes Linear Variance Adjustment for Locally Linear DLMs
Author(s) -
Wilkinson D. J.
Publication year - 1997
Publication title -
journal of forecasting
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.543
H-Index - 59
eISSN - 1099-131X
pISSN - 0277-6693
DOI - 10.1002/(sici)1099-131x(199709)16:5<329::aid-for664>3.0.co;2-6
Subject(s) - covariance , univariate , linear model , observable , bayes' theorem , series (stratigraphy) , mathematics , general linear model , variance (accounting) , econometrics , computer science , bayesian probability , statistics , multivariate statistics , economics , paleontology , physics , accounting , quantum mechanics , biology
This paper exhibits quadratic products of linear combinations of observables which identify the covariance structure underlying the univariate locally linear time series dynamic linear model. The first‐ and second‐order moments for the joint distribution over these observables are given, allowing Bayes linear learning for the underlying covariance structure for the time series model. An example is given which illustrates the methodology and highlights the practical implications of the theory. © 1997 John Wiley & Sons, Ltd.