3.9.3.1.3. statsmodels.regression.mixed_linear_model.MixedLMResults¶
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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: See statsmodels.LikelihoodModelResults
Returns: Attributes
model : class instance
Pointer to PHreg model instance that called fit.
normalized_cov_params : array
The sampling covariance matrix of the estimates
fe_params : array
The fitted fixed-effects coefficients
re_params : array
The fitted random-effects covariance matrix
bse_fe : array
The standard errors of the fitted fixed effects coefficients
bse_re : array
The standard errors of the fitted random effects covariance matrix
See also
statsmodels.LikelihoodModelResults
3.9.3.1.3.1. Methods¶
__init__ (model, params, cov_params) |
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bse () |
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bse_fe () |
Returns the standard errors of the fixed effect regression coefficients. |
bse_re () |
Returns the standard errors of the variance parameters. |
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) |
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llf () |
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load (fname) |
load a pickle, (class method) |
normalized_cov_params () |
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predict ([exog, transform]) |
Call self.model.predict with self.params as the first argument. |
profile_re (re_ix[, num_low, dist_low, ...]) |
Calculate a series of values along a 1-dimensional profile likelihood. |
pvalues () |
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random_effects () |
Returns the conditional means of all 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 |
save (fname[, remove_data]) |
save a pickle of this instance |
summary ([yname, xname_fe, xname_re, title, ...]) |
Summarize the mixed model 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. |