A results class for the discrete dependent variable models.
..Warning :
The following description has not been updated to this version/class. Where are AIC, BIC, ....? docstring looks like copy from discretemod
Parameters : | model : A DiscreteModel instance mlefit : instance of LikelihoodResults
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Returns : | *Attributes* : Warning most of these are not available yet : aic : float
bic : float
bse : array
df_resid : float
df_model : float
fitted_values : array
llf : float
llnull : float
llr : float
llr_pvalue : float
prsquared : float
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Methods
aic() | |
bic() | |
bootstrap([nrep, method, disp, store]) | simple bootstrap to get mean and variance of estimator |
bse() | |
bsejac() | standard deviation of parameter estimates based on covjac |
bsejhj() | standard deviation of parameter estimates based on covHJH |
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. |
covjac() | covariance of parameters based on outer product of jacobian of |
covjhj() | covariance of parameters based on HJJH |
df_modelwc() | |
f_test(r_matrix[, q_matrix, cov_p, scale, ...]) | Compute an Fcontrast/F-test for a contrast matrix. |
get_nlfun(fun) | |
hessv() | cached Hessian of log-likelihood |
initialize(model, params, **kwd) | |
jacv() | cached Jacobian of log-likelihood |
llf() | |
load(fname) | load a pickle, (class method) |
normalized_cov_params() | |
predict([exog]) | |
pvalues() | |
remove_data() | remove data arrays, all nobs arrays from result and model |
save(fname[, remove_data]) | save a pickle of this instance |
t([column]) | deprecated: Return the t-statistic for a given parameter estimate. |
t_test(r_matrix[, q_matrix, cov_p, scale]) | Compute a tcontrast/t-test for a row vector array of the form Rb = q |
tvalues() | Return the t-statistic for a given parameter estimate. |