Robust Estimaton Techniques for Population Parameters and Regression Coefficients.
AIR FORCE INST OF TECH WRIGHT-PATTERSON AFB OHIO SCHOOL OF ENGINEERING
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A Monte Carlo analysis is performed to determine the efficiencies of robust estimators of the location and scale parameters of the double exponential, normal, and uniform distributions relative to the maximum-likelihood estimators of the same parameters. Tables are prepared comparing the relative efficiencies of ten estimators of the location parameter and seven estimators of the scale parameter for each of the three distribution functions mentioned above. Besides the relative efficiencies, two other measures of merit are used to compare the robust estimators. These measures of merit are guaranteed efficiency and average efficiency. The Monte Carlo analysis also includes a procedure to determine the coefficients in a regression model by robust methods. The kurtosis of the residuals for the least squares regression is used as a discriminant for selecting the best method of regression. Modified author abstract
- Statistics and Probability