Journal article
Estimation of averages in truncated samples
Environmental science & technology, v 24(6), pp 912-919
01 Jan 1990
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
This paper compares methodologies for the estimation of the mean of a series of observations that contain results below a known detection limit. The bias-corrected restricted maximum likelihood method, not previously employed in environmental science and engineering, is found to be the least biased estimator, with a mean square error only slightly greater than the ordinary maximum likelihood method. This method is more robust to a variety of deviations from normality and, in particular, is better than either graphical or half detection limit methods, in most cases. It is also somewhat easier to compute than the maximum likelihood method.
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Details
- Title
- Estimation of averages in truncated samples
- Creators
- Charles Haas - Illinois Institute of TechnologyPeter Scheff - Environmental and Occupational Health Sciences
- Publication Details
- Environmental science & technology, v 24(6), pp 912-919
- Publisher
- American Chemical Society; Washington, DC
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Civil, Architectural, and Environmental Engineering
- Web of Science ID
- WOS:A1990DF92900028
- Scopus ID
- 2-s2.0-0025440550
- Other Identifier
- 991019189072704721
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- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Engineering, Environmental
- Environmental Sciences