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Abstract Details
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Activity Number:
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84
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Type:
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Contributed
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Date/Time:
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Sunday, July 31, 2011 : 4:00 PM to 5:50 PM
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Sponsor:
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Business and Economic Statistics Section
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| Abstract - #302024 |
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Title:
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Forecasting the Evolution of Curves
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Author(s):
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Sivan Aldor-Noiman*+ and Robert Stine and Lawrence Brown
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Companies:
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The Wharton School and University of Pennsylvania and University of Pennsylvania
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Address:
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Statistics Department, 3730 Walnut st., Philadelphia, PA, 19104,
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Keywords:
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forecasting repeating patterns ;
time series ;
counts process ;
crime maps ;
call centers ;
parametric and non parametric
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Abstract:
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We forecast evolving curves using a combination of parametric and nonparametric estimators. Consider the number of calls that arrive over the day at a call center or the number of crimes that occur over a geographic region during a period of time. We model these counts as a product of two processes, V and P. V is a low resolution attribute, such as daily/weekly volume while P is a high resolution attribute capturing the repeating pattern over time. Both of these processes can evolve over time (and/or space) depending on the problem at hand. The goal of this research is to forecast the one-period-ahead curve for each of these applications.
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