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_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
Last update:
Jun 10, 2024