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Inferences for the Cauchy distribution based on maximum likelihood estimators

Gerald Nicholas Haas, Lee J. Bain, Charles E. Antle

Open publisher page 54 citations

Abstract

Tables, based on maximum likelihood estimators, are presented which enable one to obtain confidence intervals and test hypotheses about parameters of the Cauchy distribution. The difficulty in obtaining the maximum likelihood estimates of the parameters is discussed. Comparisons between the maximum likelihood estimators and the best linear unbiased estimators are presented.

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What this paper is about

Tables, based on maximum likelihood estimators, are presented which enable one to obtain confidence intervals and test hypotheses about parameters of the Cauchy distribution. The difficulty in obtaining the maximum likelihood estimates of the parameters is discussed. Comparisons between the maximum likelihood estimators and the best linear unbiased estimators are presented.

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OpenAlex reports 54 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

Tables, based on maximum likelihood estimators, are presented which enable one to obtain confidence intervals and test hypotheses about parameters of the Cauchy distribution. The difficulty in obtaining the maximum likelihood estimates of the parameters is discussed. Comparisons between the maximum likelihood estimators and the best linear unbiased estimators are presented.

Key concepts: Mathematics, Cauchy distribution, Estimator, Statistics, Maximum likelihood, M-estimator, Applied mathematics

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