JSM 2005 - Toronto

Abstract #302282

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Legend: = Applied Session, = Theme Session, = Presenter
Activity Number: 427
Type: Invited
Date/Time: Wednesday, August 10, 2005 : 2:00 PM to 3:50 PM
Sponsor: WNAR
Abstract - #302282
Title: Residual-based Diagnostics for Spatial Regression Models
Author(s): Oliver Schabenberger*+ and Carol A. Gotway Crawford
Companies: SAS Institute, Inc. and Centers for Disease Control and Prevention
Address: SAS Campus Dr., Cary, NC, 27513, United States
Keywords: Correlated data ; Spatial statistics ; Generalized least squares ; Error recovery ; Semivariogram
Abstract:

Residuals from a fitted regression model form the basis for many useful empirical tools that can help identify departures from model assumptions. However, residuals are not without problems, particularly when used with spatial data. In this presentation, these problems are reviewed and potential solutions are described, including the use of linearly recovered errors and recursive residuals. Also discussed are some of the advantages and disadvantages of these methods, which are evaluated using soil carbon and nitrogen data from a precision agriculture experiment.

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Revised March 2005