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在农业生产中经常接触到的实际问题并不全是线性相关,而多数情况下是呈非线性关系。例如:降雨量与作物产量之间就不成线性关系,降雨量多了不行,少了也不行,只能有一个合适的范围,这类问题如果采用直线或平面作回归模型,显然是不符合真实情况的。只有对数据资料作非线性回归模型拟合,才能获得较为可靠的预测模型。非线性回归模型的一般形式为:
The practical problems that are often encountered in agricultural production are not all linear but in most cases nonlinear. For example, there is no linear relationship between rainfall and crop yield. If there is too much rainfall, then there is only one suitable range for less rainfall. Obviously these types of problems are not true if the regression model is straight or plane The situation. Only a non-linear regression model fitting data to obtain a more reliable prediction model. The general form of the nonlinear regression model is: