statsmodels.genmod.qif.QIFResults¶
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class
statsmodels.genmod.qif.
QIFResults
(model, params, cov_params, scale, use_t=False, **kwds)[source]¶ Results class for QIF Regression
Methods
aic
()An AIC-like statistic for models fit using QIF. bic
()A BIC-like statistic for models fit using QIF. bse
()The standard errors of the parameter estimates. conf_int
([alpha, cols, method])Returns the confidence interval of the fitted parameters. cov_params
([r_matrix, column, scale, cov_p, …])Returns the variance/covariance matrix. f_test
(r_matrix[, cov_p, scale, invcov])Compute the F-test for a joint linear hypothesis. fittedvalues
()Returns the fitted values from the model. initialize
(model, params, **kwd)Initialize (possibly re-initialize) a Results instance. llf
()Log-likelihood of model load
(fname)load a pickle, (class method); use only on trusted files, as unpickling can run arbitrary code. normalized_cov_params
()See specific model class docstring predict
([exog, transform])Call self.model.predict with self.params as the first argument. pvalues
()The two-tailed p values for the t-stats of the params. remove_data
()remove data arrays, all nobs arrays from result and model save
(fname[, remove_data])save a pickle of this instance summary
([yname, xname, title, alpha])Summarize the QIF 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. 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