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
?
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.