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Abstract Details
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Activity Number:
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514
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Type:
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Contributed
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Date/Time:
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Wednesday, August 1, 2012 : 10:30 AM to 12:20 PM
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Sponsor:
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Business and Economic Statistics Section
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| Abstract - #305571 |
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Title:
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Goodness-of-Fit Testing for Non-Causal Autoregressive Time Series with Stable Noise
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Author(s):
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Yunwei Cui*+ and Thomas Fisher and Rongning Wu
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Companies:
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University of Houston-Downtown and University of Missouri-Kansas City and Baruch College
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Address:
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Department of Computer and Mathematical, Houston, TX, 77002, United States
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Keywords:
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non-causal autoregressive ;
stable noise
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Abstract:
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We study the goodness-of-fit test for non-causal autoregressive time series with non-Gaussian stable noise. To model time series exhibiting sharp spikes or occasional bursts of outlying observations, the exponent of the non-Gaussian stable variables is assumed to be less than two. Under such conditions, the innovation variables have no finite second moment. We proved that the sample autocorrelation functions of the trimmed residuals are asymptotically normal. Thus, an assortment of portmanteau statistics are available for model assessment.
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Authors who are presenting talks have a * after their name.
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