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Robust Likelihood Calculation for Time Series

Ross H. Taplin
Journal of the Royal Statistical Society. Series B (Methodological)
Vol. 55, No. 4 (1993), pp. 829-836
Published by: Wiley for the Royal Statistical Society
Stable URL: http://www.jstor.org/stable/2345996
Page Count: 8
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Since scans are not currently available to screen readers, please contact JSTOR User Support for access. We'll provide a PDF copy for your screen reader.
Robust Likelihood Calculation for Time Series
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Abstract

We propose a computationally efficient method for calculating the likelihoods of a time series under many submodels, each of which assumes a patch of outliers or level shifts. We assume a state space representation of the time series model with a Bayesian-type treatment of anomalies. The calculations form the basis for an efficient and robust estimation procedure. The method is also applicable to linear regression with correlated errors and is illustrated with two examples.

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