Confidence Intervals Based on Robust Estimators


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ÇETİN M., Aktas S.

JOURNAL OF MODERN APPLIED STATISTICAL METHODS, cilt.7, sa.1, ss.253-258, 2008 (ESCI) identifier identifier

Özet

Classical estimation of confidence intervals based on the sample mean and variance is sensitive to outliers. Robust methods were proposed for reducing the influence of outliers. The Minimum Volume Ellipsoid estimator (MVE), having a high breakdown point, is one of the robust estimators for location and scale parameters. The robust confidence interval for location parameter is constructed based on the MVE, and compared with the proposed robust confidence interval estimation methods. The performance of the robust confidence interval based on MVE is illustrated with a simulation study. The lengths of 100(1-alpha)% confidence intervals were investigated.