Confidence Interval Robustness with Long-Tailed Symmetric Distributions
- 1 June 1976
- journal article
- research article
- Published by JSTOR in Journal of the American Statistical Association
- Vol. 71 (354) , 409
- https://doi.org/10.2307/2285324
Abstract
A variety of 95-percent confidence interval procedures have been examined in some detail using Monte Carlo techniques. These estimators were tried on simulated samples of sizes 10 and 20 from a spectrum of distributions ranging from the Gaussian to the long-tailed Cauchy. The robustness of an estimator is measured by both the closeness of its level to the 5-percent goal (robustness of validity) and its expected length as compared to its competitors (robustness of efficiency). Results include some quite robust procedures including some of the point M-estimators from the Princeton Robustness Study.Keywords
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