class statsmodels.regression.mixed_linear_model.MixedLMResults(model, params, cov_params)
[source]
Class to contain results of fitting a linear mixed effects model.
MixedLMResults inherits from statsmodels.LikelihoodModelResults
Parameters: | statsmodels.LikelihoodModelResults (See) – |
---|---|
Returns: |
|
See also
statsmodels.LikelihoodModelResults
aic () | |
bic () | |
bootstrap ([nrep, method, disp, store]) | simple bootstrap to get mean and variance of estimator |
bse () | |
bse_fe () | Returns the standard errors of the fixed effect regression coefficients. |
bse_re () | Returns the standard errors of the variance parameters. |
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 log-likelihood |
covjhj () | covariance of parameters based on HJJH |
df_modelwc () | |
f_test (r_matrix[, cov_p, scale, invcov]) | Compute the F-test for a joint linear hypothesis. |
fittedvalues () | Returns the fitted values for the model. |
get_nlfun (fun) | |
hessv () | cached Hessian of log-likelihood |
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. |
profile_re (re_ix, vtype[, num_low, …]) | Profile-likelihood inference for variance parameters. |
pvalues () | |
random_effects () | The conditional means of random effects given the data. |
random_effects_cov () | Returns the conditional covariance matrix of the random effects for each group given the data. |
remove_data () | remove data arrays, all nobs arrays from result and model |
resid () | Returns the residuals for the model. |
save (fname[, remove_data]) | save a pickle of this instance |
score_obsv () | cached Jacobian of log-likelihood |
summary ([yname, xname_fe, xname_re, title, …]) | Summarize the mixed model regression results. |
t_test (r_matrix[, 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 |
use_t |
© 2009–2012 Statsmodels Developers
© 2006–2008 Scipy Developers
© 2006 Jonathan E. Taylor
Licensed under the 3-clause BSD License.
http://www.statsmodels.org/stable/generated/statsmodels.regression.mixed_linear_model.MixedLMResults.html