Prediction by regression and intrarange data scatter in surface-process studies |
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Authors: | T. J. Toy W. R. Osterkamp K. G. Renard |
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Affiliation: | (1) Department of Geography, University of Denver, 80208 Denver, Colorado, USA;(2) Denver Federal Center, US Geological Survey, Box 25046, MS 413, 80225 Lakewood, Colorado, USA;(3) Aridland Watershed Management Research Unit, USDA Agricultural Research Service, 2000 E. Allen Road, 85719 Tucson, Arizona, USA |
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Abstract: | Modeling is a major component of contemporary earth science, and regression analysis occupies a central position in the parameterization, calibration, and validation of geomorphic and hydrologic models. Although this methodology can be used in many ways, we are primarily concerned with the prediction of values for one variable from another variable. Examination of the literature reveals considerable inconsistency in the presentation of the results of regression analysis and the occurrence of patterns in the scatter of data points about the regression line. Both circumstances confound utilization and evaluation of the models. Statisticians are well aware of various problems associated with the use of regression analysis and offer improved practices; often, however, their guidelines are not followed. After a review of the aforementioned circumstances and until standard criteria for model evaluation become established, we recommend, as a minimum, inclusion of scatter diagrams, the standard error of the estimate, and sample size in reporting the results of regression analyses for most surface-process studies. |
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Keywords: | Modeling Regression analysis Data scatter Surface-process studies |
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