class statsmodels.sandbox.regression.gmm.GMM(endog, exog, instrument, k_moms=None, k_params=None, missing='none', **kwds)
[source]
Class for estimation by Generalized Method of Moments
needs to be subclassed, where the subclass defined the moment conditions momcond
Parameters: 


Returns: 

The GMM class only uses the moment conditions and does not use any data directly. endog, exog, instrument and kwds in the creation of the class instance are only used to store them for access in the moment conditions. Which of this are required and how they are used depends on the moment conditions of the subclass.
Warning:
Options for various methods have not been fully implemented and are still missing in several methods.
TODO: currently onestep (maxiter=0) still produces an updated estimate of bse and cov_params.
calc_weightmatrix (moms[, weights_method, …])  calculate omega or the weighting matrix 
fit ([start_params, maxiter, inv_weights, …])  Estimate parameters using GMM and return GMMResults 
fitgmm (start[, weights, optim_method, …])  estimate parameters using GMM 
fitgmm_cu (start[, optim_method, optim_args])  estimate parameters using continuously updating GMM 
fititer (start[, maxiter, start_invweights, …])  iterative estimation with updating of optimal weighting matrix 
from_formula (formula, data[, subset, drop_cols])  Create a Model from a formula and dataframe. 
gmmobjective (params, weights)  objective function for GMM minimization 
gmmobjective_cu (params[, weights_method, wargs])  objective function for continuously updating GMM minimization 
gradient_momcond (params[, epsilon, centered])  gradient of moment conditions 
momcond_mean (params)  mean of moment conditions, 
predict (params[, exog])  After a model has been fit predict returns the fitted values. 
score (params, weights[, epsilon, centered])  
score_cu (params[, epsilon, centered])  
set_param_names (param_names[, k_params])  set the parameter names in the model 
start_weights ([inv]) 
endog_names  Names of endogenous variables 
exog_names  Names of exogenous variables 
results_class 
© 2009–2012 Statsmodels Developers
© 2006–2008 Scipy Developers
© 2006 Jonathan E. Taylor
Licensed under the 3clause BSD License.
http://www.statsmodels.org/stable/generated/statsmodels.sandbox.regression.gmm.GMM.html