class statsmodels.regression.quantile_regression.QuantRegResults(model, params, normalized_cov_params=None, scale=1.0, cov_type='nonrobust', cov_kwds=None, use_t=None, **kwargs)
[source]
Results instance for the QuantReg model
HC0_se () | See statsmodels.RegressionResults |
HC1_se () | See statsmodels.RegressionResults |
HC2_se () | See statsmodels.RegressionResults |
HC3_se () | See statsmodels.RegressionResults |
aic () | |
bic () | |
bse () | |
centered_tss () | |
compare_f_test (restricted) | use F test to test whether restricted model is correct |
compare_lm_test (restricted[, demean, use_lr]) | Use Lagrange Multiplier test to test whether restricted model is correct |
compare_lr_test (restricted[, large_sample]) | Likelihood ratio test to test whether restricted model is correct |
condition_number () | Return condition number of exogenous matrix. |
conf_int ([alpha, cols]) | Returns the confidence interval of the fitted parameters. |
cov_HC0 () | See statsmodels.RegressionResults |
cov_HC1 () | See statsmodels.RegressionResults |
cov_HC2 () | See statsmodels.RegressionResults |
cov_HC3 () | See statsmodels.RegressionResults |
cov_params ([r_matrix, column, scale, cov_p, …]) | Returns the variance/covariance matrix. |
eigenvals () | Return eigenvalues sorted in decreasing order. |
ess () | |
f_pvalue () | |
f_test (r_matrix[, cov_p, scale, invcov]) | Compute the F-test for a joint linear hypothesis. |
fittedvalues () | |
fvalue () | |
get_prediction ([exog, transform, weights, …]) | compute prediction results |
get_robustcov_results ([cov_type, use_t]) | create new results instance with robust covariance as default |
initialize (model, params, **kwd) | |
llf () | |
load (fname) | load a pickle, (class method) |
mse () | |
mse_model () | |
mse_resid () | |
mse_total () | |
nobs () | |
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 () | |
resid_pearson () | Residuals, normalized to have unit variance. |
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[, cov_p, scale, use_t]) | Compute a t-test for a each linear hypothesis of the form Rb = q |
t_test_pairwise (term_name[, method, alpha, …]) | perform pairwise t_test with multiple testing corrected p-values |
tvalues () | Return the t-statistic for a given parameter estimate. |
uncentered_tss () | |
wald_test (r_matrix[, cov_p, scale, invcov, …]) | Compute a Wald-test for a joint linear hypothesis. |
wald_test_terms ([skip_single, …]) | Compute a sequence of Wald tests for terms over multiple columns |
wresid () |
use_t |
© 2009–2012 Statsmodels Developers
© 2006–2008 Scipy Developers
© 2006 Jonathan E. Taylor
Licensed under the 3-clause BSD License.
http://www.statsmodels.org/stable/generated/statsmodels.regression.quantile_regression.QuantRegResults.html