Maximum likelihood estimators of population parameters from doubly left-censored samples

Autor:	Abou El-Makarim A. Aboueissa, Michael R. Stoline
Rok vydání:	2006
Předmět:	Statistics and Probability Restricted maximum likelihood Estimation theory Ecological Modeling Statistics Expectation–maximization algorithm Estimator Maximum likelihood sequence estimation M-estimator Likelihood function Likelihood principle Mathematics
Zdroj:	Environmetrics. 17:811-826
ISSN:	1099-095X 1180-4009
DOI:	10.1002/env.795
Popis:	Left-censored data often arise in environmental contexts with one or more detection limits, DLs. Estimators of the parameters are derived for left-censored data having two detection limits: DL1 and DL2 assuming an underlying normal distribution. Two different approaches for calculating the maximum likelihood estimates (MLE) are given and examined. These methods also apply to lognormally distributed environmental data with two distinct detection limits. The performance of the new estimators is compared utilizing many simulated data sets. Examples are given illustrating the use of these methods utilizing a computer program given in the Appendix. Copyright © 2006 John Wiley & Sons, Ltd.
Databáze:	OpenAIRE
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