import numpy as np
x = <your set of dependent variables>
y = <your independent variable>
cens = <the cens vector as defined in the library documentation>
tobit = TobitModel()
rTobit = tobit.fit(x, y, cens, verbose=False)
yHat = rTobit.predict(x)
yHat = yHat.reshape(yHat.shape[0],1)
yMean = np.full((yHat.shape[0],1), y.mean()[0])
cDet = np.dot(np.transpose(yHat-yMean), yHat-yMean) / np.dot(np.transpose(y-yMean), y-yMean)
您可能希望尝试以下代码,以获得确定系数,这是您需要的一个很好的指标:
Tobit回归在估计可用性百分比(范围在0到100之间)等变量时非常有用
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