statsmodels.genmod.qif.QIFResults¶
- class statsmodels.genmod.qif.QIFResults(model, params, cov_params, scale, use_t=False, **kwds)[source]¶
Results class for QIF Regression
- Attributes:
- 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.
- fittedvalues
Returns the fitted values from the model.
- llf
Log-likelihood of model
- pvalues
The two-tailed p values for the t-stats of the params.
- tvalues
Return the t-statistic for a given parameter estimate.
use_t
Flag indicating to use the Student’s distribution in inference.
Methods
conf_int
([alpha, cols])Construct confidence interval for the fitted parameters.
cov_params
([r_matrix, column, scale, cov_p, ...])Compute the variance/covariance matrix.
f_test
(r_matrix[, cov_p, invcov])Compute the F-test for a joint linear hypothesis.
initialize
(model, params, **kwargs)Initialize (possibly re-initialize) a Results instance.
load
(fname)Load a pickled results instance
See specific model class docstring
predict
([exog, transform])Call self.model.predict with self.params as the first argument.
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, 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.
wald_test
(r_matrix[, cov_p, invcov, use_f, ...])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.
Properties
An AIC-like statistic for models fit using QIF.
A BIC-like statistic for models fit using QIF.
The standard errors of the parameter estimates.
Returns the fitted values from the model.
Log-likelihood of model
The two-tailed p values for the t-stats of the params.
Return the t-statistic for a given parameter estimate.
Flag indicating to use the Student's distribution in inference.