模型预测的置信区间 [英] Confidence intervals for model prediction

问题描述

我正在关注 statsmodels 教程

一个OLS模型装有

formula = 'S ~ C(E) + C(M) + X' 
lm = ols(formula, salary_table).fit()
print lm.summary()

通过以下方式提供预测值:

Predicted values are provided through:

lm.predict({'X' : [12], 'M' : [1], 'E' : [2]})

结果作为单值数组返回.

The result is returned as a single value array.

是否有一种方法也可以返回 statsmodels 中预测值(预测区间)的置信区间?

Is there a method to also return confidence intervals for the predicted value (prediction intervals) in statsmodels?

谢谢.

推荐答案

我们一直想让这更容易获得.你应该可以使用

We've been meaning to make this easier to get to. You should be able to use

from statsmodels.sandbox.regression.predstd import wls_prediction_std
prstd, iv_l, iv_u = wls_prediction_std(results)

如果您有任何问题，请在github上提交问题.

If you have any problems, please file an issue on github.

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