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Abstract Details
Activity Number:
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623
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Type:
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Contributed
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Date/Time:
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Thursday, August 4, 2011 : 8:30 AM to 10:20 AM
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Sponsor:
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Section on Nonparametric Statistics
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Abstract - #302672 |
Title:
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Testing Parametric Assumptions of Trends of Nonstationary Time Series
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Author(s):
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Ting Zhang*+ and Wei Wu
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Companies:
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The University of Chicago and The University of Chicago
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Address:
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Department of Statistics, Chicago, IL, 60637,
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Keywords:
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Bias correction ;
Central limit theorem ;
Integrated squared errors ;
Local linear estimation ;
Locally stationary processes ;
Nonparametric hypothesis testing
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Abstract:
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We consider testing whether the mean trend of a non-stationary time series is of certain parametric forms. A central limit theorem for the integrated squared error is derived, and a simulation-based testing procedure is proposed. Our methods are illustrated in simulation studies, and applied to assess the mean pattern of lifetime-maximum wind speeds of global tropical cyclones from 1981 to 2006. We also revisit the trend pattern in the central England temperature series.
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