Abstract Details
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Activity Number:
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376
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Type:
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Contributed
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Date/Time:
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Tuesday, August 6, 2013 : 10:30 AM to 12:20 PM
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Sponsor:
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Section on Statistical Computing
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| Abstract - #309280 |
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Title:
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Bootstrapping Time Series Data
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Author(s):
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Maher Qumsiyeh*+ and Robert Deis
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Companies:
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University of Dayton and University of Dayton
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Keywords:
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Time Series ;
Autoregressive ;
Moving Average ;
Bootstrap ;
Box-Jenkins ;
SAS
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Abstract:
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We will show how the bootstrap can be used in an auto-regressive (AR) model as well as in an integrated moving average(IMA) model. We will also provide a comparison between the bootstrap and the currently used methods, such as Box-Jenkins methodology. One such comparison will be in the length of confidence intervals for the parameter estimates as well as the confidence intervals for the forecast values. All analysis and programming is done using the statistical software package SAS.
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Authors who are presenting talks have a * after their name.
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