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Abstract Details
Activity Number:
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308
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Type:
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Contributed
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Date/Time:
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Tuesday, August 2, 2011 : 8:30 AM to 10:20 AM
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Sponsor:
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Business and Economic Statistics Section
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Abstract - #302709 |
Title:
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Quantile Autocorrelation Function and Quantile Partial Autocorrelation Function
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Author(s):
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Yang Li*+
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Companies:
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University of Hong Kong
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Address:
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Department of Statistics and Actuarial Science, Hong Kong, International, , China
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Keywords:
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quantile regression ;
autocorrelation ;
partial autocorrelation ;
model specification ;
diagnostic checking
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Abstract:
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Since the pioneer research of quantile regression existed in the later decades of last century, lots of its applications followed. With noted that the quantile research on time series mainly focused on model estimation, we reconstruct some traditional statistics to verify their asymptotic properties to check the significance of estimated parameters and the randomness of errors. Encouraged by the will of working out a new system of benchmarks of time series model, we have worked on how the movements of t-th observation were influenced by its forehead observation at lag k. We figure out their by redefining the autocorrelation and partial autocorrelation function of a stationery sequence in quantile ways. We express the quantile autocorrelation function (QACF) and partial autocorrelation function (QPACF), then observe their curtail properties in order to complete the quantile identification process. Based on the new standard model specification, we deduce several new statistics under the quantile parameter estimation method and figure out their asymptotic properties to fill the diagnostic checking part of the quantile regression.
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Authors who are presenting talks have a * after their name.
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