calc_cov_params (moms, gradmoms[, weights, ...]) | calculate covariance of parameter estimates |
compare_j (other) | overidentification test for comparing two nested gmm estimates |
conf_int ([alpha, cols, method]) | Returns the confidence interval of the fitted parameters. |
cov_params (**kwds) | |
f_test (r_matrix[, cov_p, scale, invcov]) | Compute the F-test for a joint linear hypothesis. |
fittedvalues () | |
get_bse (**kwds) | standard error of the parameter estimates with options |
initialize (model, params, **kwd) | |
jtest () | overidentification test |
jval () | |
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 () | |
q () | |
remove_data () | remove data arrays, all nobs arrays from result and model |
resid () | |
save (fname[, remove_data]) | save a pickle of this instance |
ssr () | |
summary ([yname, xname, title, alpha]) | 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 |
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. |
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