Estimation of the mean and standard deviation from normally distributed singly-censored samples

Autor: Michael R. Stoline, Abou El-Makarim A. Aboueissa
Rok vydání: 2004
Předmět:
Zdroj: Environmetrics. 15:659-673
ISSN: 1099-095X
1180-4009
DOI: 10.1002/env.643
Popis: This article is concerned with the estimation of the mean μ and standard deviation σ utilizing a singly-left-censored sample of normally distributed data having a known detection limit (DL). A new computer algorithm for obtaining the Cohen (1959) maximum likelihood estimates of μ and σ is provided which does not require auxiliary tables. The algorithm utilizes S-PLUS or R languages. Closed form estimates of the mean and standard deviation obtained under a new replacement method are given for normally distributed left-censored samples, which appear to be superior to existing replacement method estimates. The replacement method estimates are based on replacing the left-censored observations by a non-constant value. The performances of these methods are compared utilizing many simulated data sets. Copyright © 2004 John Wiley & Sons, Ltd.
Databáze: OpenAIRE
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