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Abstract Details
Activity Number:
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78
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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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Section on Statistical Computing
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Abstract - #301772 |
Title:
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A Method for Simulating Univariate and Multivariate Burr Type III and Type XII Distributions with Specified L-Moments and L-Correlations
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Author(s):
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Mohan Dev Pant*+ and Todd Christopher Headrick
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Companies:
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Southern Illinois University at Carbondale and Southern Illinois University at Carbondale
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Address:
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Department of Educational Psychology, Carbondale, IL, 62901,
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Keywords:
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Monte Carlo simulation ;
L-moments ;
L-correlation ;
order statistics
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Abstract:
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Burr Type III and Type XII distributions are mainly used in statistical modeling and for simulating non-normal distributions with conventional moments (e.g. Skew, Kurtosis). However, conventional moment-based estimators can (a) be substantially biased, (b) have high variance, or (c) be influenced by outliers. In this context, a characterization of Burr distributions through the method of L-moments is introduced. Specifically, equations are derived for determining the shape parameters associated with user specified L-moment ratios (e.g. L-Skew, L-Kurtosis). A procedure is developed for generating multivariate Burr distributions with arbitrary L-correlation matrices. Numerical examples are provided to show that L-moment based Burr distributions are superior to their conventional moment based analogs in the context of distribution fitting. Monte Carlo simulation results are provided to show
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