Application of Partial Least Squares (PLS) Regression to Determine

• Activity Number: 428
• Type: Contributed
• Date/Time: Tuesday, August 3, 2010 : 2:00 PM to 3:50 PM
• Sponsor: Section on Statistics and the Environment
• Author(s): Maliha S. Nash*+ and Ricardo D. Lopez
• Companies: U.S. Environmental Protection Agency and U.S. Environmental Protection Agency
• Keywords: PLS ; CI ; Landscape ; E. Coli ; surface water ; Ozark

Abstract

Partial least squares (PLS) analysis offers a number of advantages over the traditionally used regressions applied in landscape ecology to study the associations among constituents of surface water and landscapes. Common data problems in ecological studies include: small samples, a large number of predictors, correlated variables, etc. We present here the application of PLS regression for predicting in situ surface water Escherichia coli counts from landscape metrics. The amount of variability in surface water constituents explained by each model reflects the composition of the contributing landscape metrics. The predicted values and their confidence intervals are used to explain how land cover type, configuration, and associated human activities may affect the abundance of E.coli in surface waters of the Upper White River region of the Ozark Mountains.