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March, 1982 Nonparametric Interval and Point Prediction Using Data Trimmed by a Grubbs-Type Outlier Rule
Ronald W. Butler
Ann. Statist. 10(1): 197-204 (March, 1982). DOI: 10.1214/aos/1176345702

Abstract

For a fixed probability $0 < \gamma < 1$, the "most outlying" $100(1 - \gamma){\tt\%}$ subset of the data from a location model may be located with a Grubbs outlier subset test statistic. This subset is essentially located in terms of its complement, which is the connected $100\gamma{\tt\%}$ span of the data which supports the smallest sample variance. We show that this range of the data may be characterized approximately as the $100\gamma{\tt\%}$ span such that its midpoint is equal to the trimmed mean averaged over the span. Such a range forms a tolerance interval for predicting a future observation from the location model, and the asymptotic laws for its location, coverage, and center are presented.

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Ronald W. Butler. "Nonparametric Interval and Point Prediction Using Data Trimmed by a Grubbs-Type Outlier Rule." Ann. Statist. 10 (1) 197 - 204, March, 1982. https://doi.org/10.1214/aos/1176345702

Information

Published: March, 1982
First available in Project Euclid: 12 April 2007

zbMATH: 0487.62040
MathSciNet: MR642731
Digital Object Identifier: 10.1214/aos/1176345702

Subjects:
Primary: 62G15
Secondary: 62G05, 62G35, 62M20

Rights: Copyright © 1982 Institute of Mathematical Statistics

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Vol.10 • No. 1 • March, 1982
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