The comparative R2 and its application to self-referencing models
Schlagwörter:
Coefficient of determination, R-square, self-referencing models, goodness of fit, non-linear regressionAbstract
The traditional coefficient of determination or R2 is the proportion of variation explained by a regression model versus the variation explained by the mean. This measure does not discriminate well between alternative self-referencing models such as site index curves. The traditional R2 compares the variation explained by a model with the variation about the mean dependent variable, a very simple model. A generalized R2 based on the proportion of the variation explained by the self-referencing model versus the variation explained by another simpler (yet more complicated than the mean) model provides better discrimination between candidate models. We call this generalized R2 the Comparative Coefficient of Determination or Comparative R2. Three growth series or plots from the South Africa Correlated Curve Trend Study are used to illustrate the difference between the traditional R2 and the generalized R2.
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