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Model Evaluation by Comparison of Model-Based Predictions and Measured Values

^a Crop and Soil Sciences, Cornell Univ., Ithaca, NY 14853
^b Dep. of Mathematics and Dep. of Statistical Science, Cornell Univ., Ithaca, NY 14853

View larger version (21K): [in a new window]   Fig. 1. Discrepancies between model (X) and data (Y). The first panel shows perfect equality, with Y = X, causing mean squared deviation (MSD) to equal zero. The second panel shows translation, with Y = 1 + X, causing squared bias (SB) to equal one. The third panel shows rotation, with Y = 2X, causing nonunity slope (NU) to equal two. The fourth panel shows scatter, with Y = X + (the left-most points having errors of 1 and -1), causing lack of correlation (LC) to equal 0.6667.

View larger version (33K): [in a new window]   Fig. 2. Components of mean squared deviation (MSD) for five wheat models. The three components are lack of correlation (LC), nonunity slope (NU), and squared bias (SB). These yield data are from Jamieson et al. (1998).