Detection limits of analyzing instruments are the main reason for censored observations of pollutant concentrations. An iterative least squares method for regression analyses is developed to suit the doubly censored data commonly observed in environmental engineering. The modified iterative least squares method utilizes the expected values of censored observations estimated from the probability density function of doubly censored data in a regression process. The modified method is examined for bias in the estimation of the parameters of a linear model, and in the estimation of the standard deviation of the regression. A mechanistic model for atmospheric transport and deposition of polycyclic aromatic hydrocarbons (PAHs) to a snow surface is formulated by utilizing the long-term PAH retention property of deep snowpacks. The modified iterative least squares method is applied to estimate the deposition parameters (dry deposition velocity and washout ratio) for various PAH species, since some of the PAH deposition levels were below the minimum detection limit of the analyzing instrument. The estimated parameters are examined statistically, and compare favourably with previously reported estimates of these parameters. Key words: censored data, regression, iterative least squares, PAHs, dry deposition velocity, washout ratio.
Doubly Censored Data from Two-Component Mixture of Inverse Weibull Distributions: Theory and Applications
