GMM.fititer()

statsmodels.sandbox.regression.gmm.GMM.fititer

GMM.fititer(start, maxiter=2, start_invweights=None, weights_method='cov', wargs=(), optim_method='bfgs', optim_args=None) [source]

iterative estimation with updating of optimal weighting matrix

stopping criteria are maxiter or change in parameter estimate less than self.epsilon_iter, with default 1e-6.

Parameters:	start : array starting value for parameters maxiter : int maximum number of iterations start_weights : array (nmoms, nmoms) initial weighting matrix; if None, then the identity matrix is used weights_method : {?cov?, ...} method to use to estimate the optimal weighting matrix, see calc_weightmatrix for details
Returns:	params : array estimated parameters weights : array optimal weighting matrix calculated with final parameter estimates