Results instance for the QuantReg model
Methods
| HC0_se() | |
| HC1_se() | |
| HC2_se() | |
| HC3_se() | |
| aic() | |
| bic() | |
| bse() | |
| centered_tss() | |
| compare_f_test(restricted) | use F test to test whether restricted model is correct |
| compare_lr_test(restricted) | Likelihood ratio test to test whether restricted model is correct |
| conf_int([alpha, cols]) | Returns the confidence interval of the fitted parameters. |
| cov_params([r_matrix, column, scale, cov_p, ...]) | Returns the variance/covariance matrix. |
| df_model() | |
| df_resid() | |
| ess() | |
| f_pvalue() | |
| f_test(r_matrix[, q_matrix, cov_p, scale, ...]) | Compute an F-test for a joint linear hypothesis. |
| fittedvalues() | |
| fvalue() | |
| initialize(model, params, **kwd) | |
| llf() | |
| load(fname) | load a pickle, (class method) |
| mse() | |
| mse_model() | |
| mse_resid() | |
| mse_total() | |
| nobs() | |
| norm_resid() | Residuals, normalized to have unit length and unit variance. |
| normalized_cov_params() | |
| predict([exog, transform]) | Call self.model.predict with self.params as the first argument. |
| prsquared() | |
| pvalues() | |
| remove_data() | remove data arrays, all nobs arrays from result and model |
| resid() | |
| rsquared() | |
| rsquared_adj() | |
| save(fname[, remove_data]) | save a pickle of this instance |
| scale() | |
| ssr() | |
| summary([yname, xname, title, alpha]) | Summarize the Regression Results |
| summary2([yname, xname, title, alpha, ...]) | Experimental summary function to summarize the regression results |
| t_test(r_matrix[, q_matrix, cov_p, scale]) | Compute a t-test for a joint linear hypothesis of the form Rb = q |
| tvalues() | Return the t-statistic for a given parameter estimate. |
| uncentered_tss() | |
| wresid() |