Statistical modeling of sediment and oyster PAH contamination data collected at a South Carolina estuary (complete and left-censored samples)

R. E. Thompson, E. O. Voit, G. I. Scott

Research output: Contribution to journalArticle

Abstract

This paper presents an analysis of polycyclic aromatic hydrocarbon (PAH) sediment and oyster contamination data collected at Murrells Inlet, South Carolina. Murrells Inlet is a high salinity estuary located in a heavily urbanized area south of Myrtle Beach, South Carolina. In the first part, lognormal and Weibull distributions are determined that best fit the data, as measured by P-P and Q-Q probability plots. The results indicate that the Weibull gives an adequate fit for almost all the PAH analytes considered. In fact, the Weibull almost always provides a better fit to the data than the lognormal distribution. The second part addresses issues associated with non-detection points, as they are regularly encountered in environmental analyses. In statistical terms, the existence of non-detection points corresponds to data that are left-censored. Several statistical methods for estimating the Weibull parameters from such left-censored data are explored. The overall result is in agreement with recent findings reported by other investigators: methods based on the underlying distribution of the data give more consistent results than those obtained by commonly used substitution methods.

Original languageEnglish (US)
Pages (from-to)99-119
Number of pages21
JournalEnvironmetrics
Volume11
Issue number1
DOIs
StatePublished - Jan 2000

Keywords

  • Gumbel
  • Left-censoring
  • Lognormal
  • P-P probability plots
  • PAH contamination
  • Q-Q probability plots
  • Weibull

ASJC Scopus subject areas

  • Statistics and Probability
  • Ecological Modeling

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