Python OLS中的R^2调整值不一致

我正在使用0.7.3版的

pandas.ols

函数。在使用简单回归与窗口回归时，我似乎得到了调整后的$R^2$的不一致值。例如，如果

realizedData

和

pastData

有600个条目，那么

model = pandas.ols(y = realizedData, x = pastData, intercept = 0, window = 600)

生成以下输出：-

-------------------------Summary of Regression Analysis-------------------------

Formula: Y ~ <1> + <10> + <90000>

Number of Observations:         596
Number of Degrees of Freedom:   3

R-squared:         0.6914
Adj R-squared:     0.6904

Rmse:            699.4880

F-stat (3, 593):   664.3691, p-value:     0.0000

Degrees of Freedom: model 2, resid 593

-----------------------Summary of Estimated Coefficients------------------------
      Variable       Coef    Std Err     t-stat    p-value    CI 2.5%   CI 97.5%
--------------------------------------------------------------------------------
             1     0.4171     0.0428       9.75     0.0000     0.3333     0.5010
            10     0.4362     0.0688       6.34     0.0000     0.3014     0.5709
         90000     0.0623     0.0319       1.95     0.0517    -0.0003     0.1249
---------------------------------End of Summary---------------------------------

给出：-

-------------------------Summary of Regression Analysis-------------------------

Formula: Y ~ <1> + <10> + <90000>

Number of Observations:         596
Number of Degrees of Freedom:   3

R-squared:         0.6914
Adj R-squared:     0.3053

Rmse:            699.4880

F-stat (3, 593):     1.7909, p-value:     0.1477

Degrees of Freedom: model 2, resid 593

-----------------------Summary of Estimated Coefficients------------------------
      Variable       Coef    Std Err     t-stat    p-value    CI 2.5%   CI 97.5%
--------------------------------------------------------------------------------
             1     0.4171     0.0428       9.75     0.0000     0.3333     0.5010
            10     0.4362     0.0688       6.34     0.0000     0.3014     0.5709
         90000     0.0623     0.0319       1.95     0.0517    -0.0003     0.1249
---------------------------------End of Summary---------------------------------

----------------------------回归分析总结-------------------------
公式：Y~++
观察次数：596
自由度：3
R平方：0.6914
调整R平方：0.3053
Rmse:699.4880
F-stat（3593）：1.7909，p-value:0.1477
自由度：模型2，剩余593
-----------------------估计系数摘要------------------------
可变系数标准误差t-stat p值CI 2.5%CI 97.5%
--------------------------------------------------------------------------------
1     0.4171     0.0428       9.75     0.0000     0.3333     0.5010
10     0.4362     0.0688       6.34     0.0000     0.3014     0.5709
90000     0.0623     0.0319       1.95     0.0517    -0.0003     0.1249
---------------------------------摘要结束---------------------------------

请注意，除了调整后的$R^2$值外，输出是相同的

---

这是一个bug还是我做错了什么？

我认为这与没有拦截有关。你能在GitHub上报告一个问题吗？

我认为这与缺少拦截有关。你能在GitHub上报告一个问题吗

-------------------------Summary of Regression Analysis-------------------------

Formula: Y ~ <1> + <10> + <90000>

Number of Observations:         596
Number of Degrees of Freedom:   3

R-squared:         0.6914
Adj R-squared:     0.3053

Rmse:            699.4880

F-stat (3, 593):     1.7909, p-value:     0.1477

Degrees of Freedom: model 2, resid 593

-----------------------Summary of Estimated Coefficients------------------------
      Variable       Coef    Std Err     t-stat    p-value    CI 2.5%   CI 97.5%
--------------------------------------------------------------------------------
             1     0.4171     0.0428       9.75     0.0000     0.3333     0.5010
            10     0.4362     0.0688       6.34     0.0000     0.3014     0.5709
         90000     0.0623     0.0319       1.95     0.0517    -0.0003     0.1249
---------------------------------End of Summary---------------------------------