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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Main Author: Chow, Hwee Kwan
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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spelling sg-smu-ink.soe_research-14612010-09-23T05:48:03Z M-Estimation of Scale Parameters in a Structural Time Series Model Chow, Hwee Kwan 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. 1996-01-01T08:00:00Z text https://ink.library.smu.edu.sg/soe_research/462 Research Collection School Of Economics eng Institutional Knowledge at Singapore Management University Econometrics
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Econometrics
spellingShingle Econometrics
Chow, Hwee Kwan
M-Estimation of Scale Parameters in a Structural Time Series Model
description 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.
format text
author Chow, Hwee Kwan
author_facet Chow, Hwee Kwan
author_sort Chow, Hwee Kwan
title M-Estimation of Scale Parameters in a Structural Time Series Model
title_short M-Estimation of Scale Parameters in a Structural Time Series Model
title_full M-Estimation of Scale Parameters in a Structural Time Series Model
title_fullStr M-Estimation of Scale Parameters in a Structural Time Series Model
title_full_unstemmed M-Estimation of Scale Parameters in a Structural Time Series Model
title_sort m-estimation of scale parameters in a structural time series model
publisher Institutional Knowledge at Singapore Management University
publishDate 1996
url https://ink.library.smu.edu.sg/soe_research/462
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