Comparison of robust estimates of modified variants of standard deviation and average absolute deviations
We study robust estimates of the scale parameter, which characterizes the “spread” of a random variable. Estimates are proposed that are asymptotically normally distributed, have limited influence functions and, therefore, in contrast to the standard deviation estimate, are “protected” from the presence of outliers in the sample. Estimates are calculated on the basis of ordered statistics, from which part of the observations is preliminarily removed. An adaptive version of estimates based on the use of sample estimates of functionals characterizing the degree of "tail-length" distributions is proposed. The results of comparing the estimates of the scale parameter under the conditions of various observation models are presented. In particular, a Gaussian model with large-scale contamination is used to describe the presence of outliers in the sample.
Keywords
scale parameter,
robust estimates,
outliers,
influence function,
adaptive estimatesAuthors
| Shulenin V.P. | National Research Tomsk State University | |
Всего: 1
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