Question

我有这样的代码

m2=smf.ols(formula='demand~year+C(months)+year*C(months)',data=df).fit()
m2.summary()

一个数据帧，具有三列，144行，需求，在2000-2011年和1-12个月。现在，我想获得基于年与月之间的交互作用的预测值，以此来预测需求（这里将月视为分类变量。该怎么办？

m2.predict( #what should I enter here?)

这里是线性回归的模型。如果有帮助

 OLS Regression Results
    Dep. Variable:  demand  R-squared:  0.985
    Model:  OLS Adj. R-squared: 0.982
    Method: Least Squares   F-statistic:    343.4
    Date:   Thu, 08 Oct 2020    Prob (F-statistic): 2.78e-98
    Time:   00:38:14    Log-Likelihood: -590.64
    No. Observations:   144 AIC:    1229.
    Df Residuals:   120 BIC:    1301.
    Df Model:   23      
    Covariance Type:    nonrobust       
    coef    std err t   P>|t|   [0.025  0.975]
    Intercept   -5.548e+04  2686.757    -20.651 0.000   -6.08e+04   -5.02e+04
    C(months)[T.2]  6521.6434   3799.648    1.716   0.089   -1001.396   1.4e+04
    C(months)[T.3]  217.7471    3799.648    0.057   0.954   -7305.292   7740.786
    C(months)[T.4]  -3200.2960  3799.648    -0.842  0.401   -1.07e+04   4322.743
    C(months)[T.5]  -7465.9988  3799.648    -1.965  0.052   -1.5e+04    57.040
    C(months)[T.6]  -1.832e+04  3799.648    -4.822  0.000   -2.58e+04   -1.08e+04
    C(months)[T.7]  -3.072e+04  3799.648    -8.086  0.000   -3.82e+04   -2.32e+04
    C(months)[T.8]  -3.013e+04  3799.648    -7.929  0.000   -3.77e+04   -2.26e+04
    C(months)[T.9]  -1.265e+04  3799.648    -3.328  0.001   -2.02e+04   -5122.469
    C(months)[T.10] -5374.5897  3799.648    -1.414  0.160   -1.29e+04   2148.449
    C(months)[T.11] 3139.5781   3799.648    0.826   0.410   -4383.461   1.07e+04
    C(months)[T.12] -1122.9114  3799.648    -0.296  0.768   -8645.950   6400.127
    year    27.7867 1.340   20.741  0.000   25.134  30.439
    year:C(months)[T.2] -3.2552 1.895   -1.718  0.088   -7.006  0.496
    year:C(months)[T.3] -0.0944 1.895   -0.050  0.960   -3.846  3.657
    year:C(months)[T.4] 1.6084  1.895   0.849   0.398   -2.143  5.360
    year:C(months)[T.5] 3.7378  1.895   1.973   0.051   -0.013  7.489
    year:C(months)[T.6] 9.1713  1.895   4.841   0.000   5.420   12.923
    year:C(months)[T.7] 15.3741 1.895   8.115   0.000   11.623  19.125
    year:C(months)[T.8] 15.0769 1.895   7.958   0.000   11.326  18.828
    year:C(months)[T.9] 6.3357  1.895   3.344   0.001   2.584   10.087
    year:C(months)[T.10]    2.6923  1.895   1.421   0.158   -1.059  6.444
    year:C(months)[T.11]    -1.5699 1.895   -0.829  0.409   -5.321  2.181
    year:C(months)[T.12]    0.5699  1.895   0.301   0.764   -3.181  4.321

Answer 1

m2.predict(df.loc[:,['year', 'months']])

通过统计模型中的互动来预测价值

1 个答案: