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Confidence Regions for Location and Scale Parameters Based on the Kolmogorov-Smirnov Goodness of Fit Statistic

Ramon C. Littell, P. V. Rao

Open publisher page 18 citations

Abstract

Computational methods are derived which permit the construction of confidence regions and intervals for location and scale parameters in a specified family of continuous distributions. The methods, which follow the procedures proposed by Barr and Davidson [1] and Easterling [2], are based on the Kolmogorov-Smirnov goodness of fit statistic, and are readily adapted to type II censored samples.

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What this paper is about

Computational methods are derived which permit the construction of confidence regions and intervals for location and scale parameters in a specified family of continuous distributions. The methods, which follow the procedures proposed by Barr and Davidson [1] and Easterling [2], are based on the Kolmogorov-Smirnov goodness of fit statistic, and are readily adapted to type II censored samples.

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Available abstract

Computational methods are derived which permit the construction of confidence regions and intervals for location and scale parameters in a specified family of continuous distributions. The methods, which follow the procedures proposed by Barr and Davidson [1] and Easterling [2], are based on the Kolmogorov-Smirnov goodness of fit statistic, and are readily adapted to type II censored samples.

Key concepts: Goodness of fit, Statistic, Kolmogorov–Smirnov test, Statistics, Confidence interval, Mathematics, Scale (ratio), Ancillary statistic

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