statsmodels.sandbox.regression.gmm.IVGMM
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class statsmodels.sandbox.regression.gmm.IVGMM(endog, exog, instrument, k_moms=None, k_params=None, missing='none', **kwds)
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Basic class for instrumental variables estimation using GMM
A linear function for the conditional mean is defined as default but the methods should be overwritten by subclasses, currently
LinearIVGMM
andNonlinearIVGMM
are implemented as subclasses.See also
Methods
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 fitstart
()from_formula
(formula, data[, subset])Create a Model from a formula and dataframe. get_error
(params)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
(params)momcond_mean
(params)mean of moment conditions, predict
(params[, exog])score
(params, weights[, epsilon, centered])score_cu
(params[, epsilon, centered])start_weights
([inv])Attributes
endog_names
exog_names
results_class
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