5.14.2.5. statsmodels.sandbox.sysreg.SysResults

class statsmodels.sandbox.sysreg.SysResults(model, params, normalized_cov_params=None, scale=1.0)[source]

Not implemented yet.

__init__(model, params, normalized_cov_params=None, scale=1.0)[source]

5.14.2.5.1. Methods

__init__(model, params[, ...])
bse()
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.
initialize(model, params, **kwd)
llf()
load(fname) load a pickle, (class method)
normalized_cov_params()
predict([exog, transform]) Call self.model.predict with self.params as the first argument.
pvalues()
remove_data() remove data arrays, all nobs arrays from result and model
save(fname[, remove_data]) save a pickle of this instance
t_test(r_matrix[, cov_p, scale, use_t]) Compute a t-test for a each linear hypothesis of the form Rb = q
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.

5.14.2.5.2. Attributes

use_t