statsmodels.sandbox.regression.gmm.NonlinearIVGMM.fitgmm

NonlinearIVGMM.fitgmm(start, weights=None, optim_method='bfgs', optim_args=None)

estimate parameters using GMM

Parameters:

• start (array_like) – starting values for minimization
• weights (array) – weighting matrix for moment conditions. If weights is None, then the identity matrix is used

Returns:

paramest – estimated parameters

Return type:

array

Notes

todo: add fixed parameter option, not here ???

uses scipy.optimize.fmin