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Evaluation of a Depth-Based Multivariate -Nearest Neighbor Resampling Method with Stormwater Quality Data

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  • Taesam Lee
  • Taha B. M. J. Ouarda
  • Fateh Chebana
  • Daeryong Park

Abstract

A nonparametric simulation model ( -nearest neighbor resampling, KNNR) for water quality analysis involving geographic information is suggested to overcome the drawbacks of parametric models. Geographic information is, however, not appropriately handled in the KNNR nonparametric model. In the current study, we introduce a novel statistical notion, called a “depth function,†in the classical KNNR model to appropriately manipulate geographic information in simulating stormwater quality. An application is presented for a case study of the total suspended solids throughout the entire United States. The stormwater total suspended solids concentration data indicated that the proposed model significantly improves the simulation performance compared with the existing KNNR model.

Suggested Citation

  • Taesam Lee & Taha B. M. J. Ouarda & Fateh Chebana & Daeryong Park, 2014. "Evaluation of a Depth-Based Multivariate -Nearest Neighbor Resampling Method with Stormwater Quality Data," Mathematical Problems in Engineering, Hindawi, vol. 2014, pages 1-7, May.
    • Handle: RePEc:hin:jnlmpe:404198
    DOI: 10.1155/2014/404198
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