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Biometrika 1977 64(1):123-128; doi:10.1093/biomet/64.1.123
© 1977 by Biometrika Trust
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Simple and highly efficient estimators for a type I censored normal sample

TORE PERSSON and HOLGER ROOTZÉN

Department of Mathematical Statistics, University of Lund Sweden

In a type Ileft censored normal sample the information consists of the observations x1, ...,xk, which fell above the ‘obsarvation limit’ c and of the number, n – k, of those observations which fell below, c. This paper considers the estimation of the parmeters of a normal population given a sample which has been censored at the known point c. When the maximum likelihood method is used to produce estimates of µ and {sigma} one has to resort to numerical solution of the resulting equations. In this paper simple estimators µ* and {sigma}* are presented. They are shown to be almost as good as the maximum likelihood estimators both for small and large samples.

Key Words: Maximum likelihood estimator • Normal distribution • Point estimator • Type I censoring


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