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Methods for Estimating Uncertainty in Factor Analytic Solutions
Citation:
Paatero, P., S. Eberly, S. Brown, AND G. Norris. Methods for Estimating Uncertainty in Factor Analytic Solutions. Atmospheric Measurement Techniques. Copernicus Publications, Katlenburg-Lindau, Germany, 7(3):781-797, (2014).
Impact/Purpose:
The National Exposure Research Laboratory′s (NERL′s) Human Exposure and Atmospheric Sciences Division (HEASD) conducts research in support of EPA′s mission to protect human health and the environment. HEASD′s research program supports Goal 1 (Clean Air) and Goal 4 (Healthy People) of EPA′s strategic plan. More specifically, our division conducts research to characterize the movement of pollutants from the source to contact with humans. Our multidisciplinary research program produces Methods, Measurements, and Models to identify relationships between and characterize processes that link source emissions, environmental concentrations, human exposures, and target-tissue dose. The impact of these tools is improved regulatory programs and policies for EPA.
Description:
The EPA PMF (Environmental Protection Agency positive matrix factorization) version 5.0 and the underlying multilinear engine-executable ME-2 contain three methods for estimating uncertainty in factor analytic models: classical bootstrap (BS), displacement of factor elements (DISP), and bootstrap enhanced by displacement of factor elements (BSDISP). The goal of these methods is to capture the uncertainty of PMF analyses due to random errors and rotational ambiguity. It is shown that the three methods complement each other: depending on characteristics of the data set, one method may provide better results than the other two. Results are presented using synthetic data sets, including interpretation of diagnostics, and recommendations are given for parameters to report when documenting uncertainty estimates from EPA PMF or ME-2 applications.
URLs/Downloads:
SUPPLEMENTAL MATERIAL_EE1_30JUL.PDF (PDF, NA pp, 68.179 KB, about PDF)FINAL FINAL ERROR_ESTIMATION_THEORY_13JAN.PDF (PDF, NA pp, 168.735 KB, about PDF)