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pythonpandaslinear-regressionstatsmodels

How to extract the regression coefficient from statsmodels.api?

 result = sm.OLS(gold_lookback, silver_lookback ).fit()

After I get the result, how can I get the coefficient and the constant?

In other words, if y = ax + c how to get the values a and c?

Solution

  • You can use the params property of a fitted model to get the coefficients.

    For example, the following code:

    import statsmodels.api as sm
import numpy as np
np.random.seed(1)
X = sm.add_constant(np.arange(100))
y = np.dot(X, [1,2]) + np.random.normal(size=100)
result = sm.OLS(y, X).fit()
print(result.params)

    will print you a numpy array [ 0.89516052 2.00334187] - estimates of intercept and slope respectively.

    If you want more information, you can use the object result.summary() that contains 3 detailed tables with model description.