statsmodels.sandbox.regression.gmm.NonlinearIVGMM.fititer¶
-
NonlinearIVGMM.
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_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 : ndarray
estimated parameters
weights : ndarray
optimal weighting matrix calculated with final parameter estimates