Variance estimation for multivariate dynamic linear models
Article Abstract:
The estimation of unknown variances in multivariate dynamic linear models is discussed. The method uses approximate conjugate analyses based on simple analytic approximation. The procedure was compared with a method based on the Robust filter. Results showed that the method is applicable to the sub-class of conjugate models. In addition, its one-step forecast errors were similar to those of the original method. The new method showed improvements in analyzing variances over the previous methods.
Publication Name: Journal of Forecasting
Subject: Mathematics
ISSN: 0277-6693
Year: 1992
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Bayes linear variance adjustment for locally linear DLMs
Article Abstract:
Proper variance specifications are vital to the performance of dynamic linear models (DLMs). Nonetheless, right specifications for other variance components are equally essential. The Bayes linear variance adjustment is used on locally linear DLMs to exhibit quadratic results of linear combinations of observables.
Publication Name: Journal of Forecasting
Subject: Mathematics
ISSN: 0277-6693
Year: 1997
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Bias in the estimation of non-linear transformation of the integrated variance of returns
Article Abstract:
An analytical approximation for the unconditional bias of estimators of non-linear transformations of integrated variance is derived.
Publication Name: Journal of Forecasting
Subject: Mathematics
ISSN: 0277-6693
Year: 2006
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