Bedoukian   RussellIPM   RussellIPM   Piezoelectric Micro-Sprayer


Home
Animal Taxa
Plant Taxa
Semiochemicals
Floral Compounds
Semiochemical Detail
Semiochemicals & Taxa
Synthesis
Control
Invasive spp.
References

Abstract

Guide

Alphascents
Pherobio
InsectScience
E-Econex
Counterpart-Semiochemicals
Print
Email to a Friend
Kindly Donate for The Pherobase

« Previous AbstractEvaluation of tetraglyme for the enrichment and analysis of volatile organic compounds in air    Next AbstractFrequency of aggregation substance and cytolysin genes among enterococcal endocarditis isolates »

J Chromatogr A


Title:How to estimate moments and quantiles of environmental data sets with non-detected observations? A case study on volatile organic compounds in marine water samples
Author(s):Huybrechts T; Thas O; Dewulf J; Van Langenhov H;
Address:"Department of Organic Chemistry, Faculty of Agricultural and Applied Biological Sciences, Ghent University, Coupure Links 653, B-9000, Ghent, Belgium"
Journal Title:J Chromatogr A
Year:2002
Volume:975
Issue:1
Page Number:123 - 133
DOI: 10.1016/s0021-9673(02)01327-4
ISSN/ISBN:0021-9673 (Print) 0021-9673 (Linking)
Abstract:"Concentrations of 27 priority volatile organic compounds were measured in water samples of the North Sea and Scheldt estuary during a 3-year monitoring study. Despite the use of a sensitive analytical method, a number of data were censored. That is, some concentrations were below the decision limit or critical level defined by IUPAC. To characterize the observed measurement results, an attempt was made to identify an appropriate procedure to compute summary statistics for the censored data sets. Several parametric and robust parametric approaches based on the maximum likelihood principle and probability-plot regression method were evaluated for the estimation of the mean, standard deviation, median and interquartile range using three uncensored analytes (1,1,2-trichloroethane, tetrachloroethene and o-xylene) from the monitoring survey. Performance was assessed by artificially censoring the observed concentrations and estimating moments and quantiles at each censoring level. Results showed that methods with the least distributional assumptions, such as the robust bias-corrected restricted maximum likelihood method, perform best for estimating the mean and standard deviation, while both parametric and robust parametric techniques can be used for quantiles. Hence, summary statistics could be estimated with little bias (5-10%) up to 80% of censoring for the data sets employed in this study"
Keywords:"Likelihood Functions Organic Chemicals/*analysis Seawater/*chemistry Sensitivity and Specificity Volatilization Water Pollutants, Chemical/*analysis;"
Notes:"MedlineHuybrechts, Tom Thas, Olivier Dewulf, Jo Van Langenhov, Herman eng Research Support, Non-U.S. Gov't Netherlands 2002/12/03 J Chromatogr A. 2002 Oct 25; 975(1):123-33. doi: 10.1016/s0021-9673(02)01327-4"

 
Back to top
 
Citation: El-Sayed AM 2024. The Pherobase: Database of Pheromones and Semiochemicals. <http://www.pherobase.com>.
© 2003-2024 The Pherobase - Extensive Database of Pheromones and Semiochemicals. Ashraf M. El-Sayed.
Page created on 06-07-2024