M-Estimation of Scale Parameters in a Structural Time Series Model
We develop scale estimators of a structural time series model which are robust towards additive outliers. This is done by extending the application of the $M$-estimation technique to the scale estimation problem in time series data. A Monte Carlo experiment is carried out to study the robust propert...
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| Format: | text |
| Language: | English |
| Published: |
Institutional Knowledge at Singapore Management University
1996
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| Online Access: | https://ink.library.smu.edu.sg/soe_research/462 |
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| Institution: | Singapore Management University |
| Language: | English |
| Summary: | We develop scale estimators of a structural time series model which are robust towards additive outliers. This is done by extending the application of the $M$-estimation technique to the scale estimation problem in time series data. A Monte Carlo experiment is carried out to study the robust properties of the proposed estimators. The simulation results indicate that the proposed $M$-estimators clearly outperform the maximum likelihood estimators produced by the Kalman filter when the observations are contaminated by outliers. |
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