get CI of r-squared

gistfile1.txt

rsquared_boot, coefs_boot, sims = [], [], 1000
reg_fit = sm.OLS(df['y'], df.iloc[:,1:]).fit()

# Run 1K iterations
for i in range(sims):
    # First create a bootstrap sample with replacement with n=df.shape[0]
    bootstrap = df.sample(n=df.shape[0], replace=True)
    # Fit the regression and append the r square to rsquared_boot
    rsquared_boot.append(sm.OLS(bootstrap['y'],bootstrap.iloc[:,1:]).fit().rsquared)

# Calculate 95% CI on rsquared_boot
print("R Squared 95% CI = {}".format(np.percentile(rsquared_boot, [2.5, 97.5])))