Fitting human exposure data with the Johnson S(B) distribution.
Exposure evaluations for epidemiological investigations and risk assessments may require estimates of background concentrations and peak exposures, as well as the population mean and variance. The S(B) distribution is a theoretically appealing probability function for characterizing ratios, and random variables bound by extremes, such as human exposures and environmental concentrations. However, fitting the parameters of this distribution with maximum likelihood methods is often problematic, and some alternative methods are examined here. Two methods based on percentiles, a quantile estimator, and a method-of-moments fitting procedure are explored. The quantile and method-of-moments procedures are based on new explicit expressions for the first four moments of this distribution. The fitting procedures are compared by simulation, and with actual data sets consisting of measurements of human exposure to airborne contaminants.
Flynn
Michael R
MR
Department of Environmental Sciences and Engineering, School of Public Health, University of North Carolina, CB 7431 Rosenau Hall, Chapel Hill, NC 27599-7431, USA. mike_flynn@unc.edu
D004781:Environmental Exposure; D004785:Environmental Pollutants / Q000633:toxicity*; D016021:Epidemiologic Studies; D006801:Humans; D015233:Models, Statistical; D018570:Risk Assessment
D004785:Environmental Pollutants