Python ARIMA 输出 - 解释 Sigma2

Python ARIMA output - interpreting Sigma2

我正在尝试解释下面的 ARIMA 输出,但不清楚 sigma2。文档说它是 'The variance of the residuals.'。这个 output/importance 背后的假设是什么?

请提供答案或 link 详细介绍的地方。

import statsmodels.api as sm
mod = sm.tsa.statespace.SARIMAX(df.Sales, order=(0, 1, 1), 
seasonal_order=(0, 1, 1, 12), enforce_stationarity=False,
                            enforce_invertibility=False)
results = mod.fit()
print(results.summary().tables[1])



   ==============================================================================
                     coef    std err          z      P>|z|      [0.025      0.975]
    ------------------------------------------------------------------------------
    ma.L1         -0.9317      0.055    -16.989      0.000      -1.039      -0.824
    ma.S.L12      -0.0851      0.143     -0.594      0.553      -0.366       0.196
    sigma2      1.185e+09   2.13e-11   5.56e+19      0.000    1.19e+09    1.19e+09
    ==============================================================================

是的,你说得对,sigma squared 表示残差值的方差。该值用于测试残差对 non-normality.

替代项的正态性

更多信息,你可以查看这个PR:https://github.com/statsmodels/statsmodels/pull/2431

和此质量检查:https://github.com/statsmodels/statsmodels/issues/2507#:~:text=The%20sigma2%20output%20in%20the,variance%20of%20the%20error%20term