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Maximum likelihood estimators of population parameters from doubly left‐censored samples
Author(s) -
Aboueissa Abou ElMakarim A.,
Stoline Michael R.
Publication year - 2006
Publication title -
environmetrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.68
H-Index - 58
eISSN - 1099-095X
pISSN - 1180-4009
DOI - 10.1002/env.795
Subject(s) - estimator , statistics , maximum likelihood , mathematics , population , m estimator , computer science , demography , sociology
Abstract 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: DL 1 and DL 2 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.