Dynamic linear model diagnostics
Journal Article (Journal Article)
SUMMARY: In time series analysis using dynamic linear models, retrospective analysis involves the calculation of filtered, or smoothed, distributions for state parameters in the past. We develop and illustrate novel results that are useful in retrospective assessment of the influence of individual observations on such distributions. In particular, new and computationally simple filtering equations are derived for past state parameters based on leaving out one observation at a time, providing dynamic model based versions of methods currently used in standard, static regression diagnostics. © 1991 Biometrika Trust.
Full Text
Duke Authors
Cited Authors
- Harrison, J; West, M
Published Date
- December 1, 1991
Published In
Volume / Issue
- 78 / 4
Start / End Page
- 797 - 808
International Standard Serial Number (ISSN)
- 0006-3444
Digital Object Identifier (DOI)
- 10.1093/biomet/78.4.797
Citation Source
- Scopus