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Title: Positive random variables with a discrete probability mass at the origin: Parameter estimation for left-censored samples with application to air quality monitoring data

Technical Report ·
OSTI ID:6078292

The concentration of a contaminant measured in a particular medium might be distributed as a positive random variable when it is present, but it may not always be present. If there is a level below which the concentration cannot be distinguished from zero by the analytical apparatus, a sample from such a population will be censored on the left. The presence of both zeros and positive values in the censored portion of such samples complicates the problem of estimating the parameters of the underlying positive random variable and the probability of a zero observation. Using the method of maximum likelihood, it is shown that the solution to this estimation problem reduces largely to that of estimating the parameters of the distribution truncated at the point of censorship. The maximum likelihood estimate of the proportion of zero values follows directly. The derivation of the maximum likelihood estimates for a lognormal population with zeros is given in detail, and the asymptotic properties of the estimates are examined. The estimation method was used to fit several different distributions to a set of severely censored /sup 85/Kr monitoring data from six locations at the Savannah River Plant chemical separations facilities.

Research Organization:
USDOE Environmental Measurements Lab., New York
OSTI ID:
6078292
Report Number(s):
EML-459; ON: DE87013826
Resource Relation:
Other Information: Portions of this document are illegible in microfiche products
Country of Publication:
United States
Language:
English