statsmodels.sandbox.regression.gmm.IVGMM.fititer#
- IVGMM.fititer(start, maxiter=2, start_invweights=None, weights_method='cov', wargs=(), optim_method='bfgs', optim_args=None)#
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
ndarray starting value for parameters
- maxiter
int maximum number of iterations
- start_invweights
array(nmoms,nmoms) initial inverse 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
- wargs
tupleordict required and optional arguments for weights_method, see calc_weightmatrix for details
- optim_method
str,defaultis‘bfgs’ numerical optimization method used in fitgmm for each iteration. Currently not all optimizers that are available in LikelihoodModels are connected.
- optim_args
dict keyword arguments for the numerical optimizer.
- start
- Returns: