Abstract Details
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Activity Number:
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239
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Type:
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Contributed
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Date/Time:
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Monday, August 5, 2013 : 2:00 PM to 3:50 PM
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Sponsor:
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Biometrics Section
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| Abstract - #309487 |
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Title:
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Estimating Kurtosis and Approximate Confidence Intervals for Variance Components
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Author(s):
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Brent Burch*+
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Companies:
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Northern Arizona Univ
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Keywords:
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Interval estimation ;
Kurtosis ;
Non-normal distributions ;
Variance
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Abstract:
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Exact confidence intervals for variance components rely on normal distribution assumptions. However, large-sample confidence intervals for variances can be realized if one estimates the kurtosis of the associated distribution. The method used to estimate kurtosis has a direct impact on the performance of the interval and thus the quality of the inferences made in finite-sample size applications. In this presentation the author considers a number of kurtosis estimators and conducts simulation studies to determine the coverage probabilities of the resulting confidence intervals. The coverage probabilities are computed for a variety of sample sizes and distributions.
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Authors who are presenting talks have a * after their name.
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