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* The quality of a regression equation is given, in addition to the statistics (R, R2, coefficients significantly different from 0), by the average error of estimated yields. * The quality of a regression equation is given, in addition to the statistics (R, R2, coefficients significantly different from 0), by the average error of estimated yields.
* Trends MUST be removed before carrying out the regression work proper. The trends need not be linear. * Trends MUST be removed before carrying out the regression work proper. The trends need not be linear.
-* Be aware of the fact that there are two types of variables: continuous quantitative ones (e.g. minimum temperature affecting crops through night-time+* Be aware of the fact that there are two types of variables: continuous quantitative ones (e.g. minimum temperature affecting crops through night-time respiration) and qualitative ones (e.g. male sterility induced by high temperatures).
-respiration) and qualitative ones (e.g. male sterility induced by high temperatures).+
* Always use a variable which stands for the local yield potential * Always use a variable which stands for the local yield potential
* A yield function does not have to be linear. In some cases, a multiplicative function can be more appropriate. * A yield function does not have to be linear. In some cases, a multiplicative function can be more appropriate.

Revision as of 10:40, 22 September 2006

Using Yield functions

The present note tries to summarise some of the considerations which the crop forecaster should keep in mind when deriving multiple regression equations (so-called Yield Functions) which will eventually be used for forecasting crop yields. The process by which the coefficients of a yield function are derived are known as calibration15. The rules below are purely empirical or based on common sense:

Some additional advice

“automatic”) addition of variables to techniques with deletion of variables;

series);


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