One-sided simultaneous tolerance limits for regression
作者:
Robert E. Odeh,
Robert W. Mee,
期刊:
Communications in Statistics - Simulation and Computation
(Taylor Available online 1990)
卷期:
Volume 19,
issue 2
页码: 663-680
ISSN:0361-0918
年代: 1990
DOI:10.1080/03610919008812881
出版商: Marcel Dekker, Inc.
关键词: calibration;discrimination;percentile;simultaneous inference
数据来源: Taylor
摘要:
Mee, Eberhardt, and Reeve (1989) recently produced tables of factors for simultaneous two-sided tolerance intervals for linear regression. These factors, obtained using numerical quadrature, provide narrower intervals than were previously available. Using identical notation, this article presents simultaneous one-sided tolerance limits for regression models. Since one-sided tolerance limits are equivalent to one-sided confidence limits on percentiles, the bounds proposed here provide simultaneous one-sided confidence limits for a specified percentile of the conditional distributions of the dependent variable. Although this specific problem had not been addressed previously in the literature, several authors have proposed simultaneous two-sided confidence intervals for a specified percentile of the dependent variable in regression (Steinhorst and Bowden 1971 ; Thomas and Thomas 1986; Turner and Bowden 1977). The limits proposed here have several applications to calibration (or discrimination). For example, one use is the construction of one-sided confidence limits for future unobserved values of the independent variable. The analogous two-sided inference in calibration has been discussed by Lieberman, Miller and Hamilton (1967) and Scheffe' (1973).
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