title: Application of robust statistical methods to background tracer data characterized by outliers and left-censored data.
abstract: Accurate analysis of tracer-breakthrough curves is dependent on the removal of measured background concentrations from the measured tracer recovery data. Background concentrations are commonly converted to a single mean background concentration that is subtracted from tracer recovery data. To obtain an improved estimate for the mean background concentration, a statically-robust procedure addressing left-censored data and possible outliers in background concentration data is presented. A maximum likelihood estimate and other robust methods coupled with outlier removal are applied. Application of statically-robust procedures to background concentrations results not only in better estimates for mean background concentration but also results in more accurate quantitative analyses of tracer-breakthrough curves when the mean background concentration is subtracted.
authors.affiliation: U.S. Environmental Protection Agency, National Center for Environmental Assessment (8623P), 1200 Pennsylvania, Ave., N.W. Washington, DC 20460, USA. field.malcolm@epa.gov
authors.forename: Malcolm S
authors.initials: MS
authors.lastname: Field
mesh_terms: D007553:Isotope Labeling / Q000379:methods*; D015233:Models, Statistical; D013997:Time Factors