statsmodels.sandbox.regression.gmm.LinearIVGMM.fititer
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LinearIVGMM.fititer(start, maxiter=2, start_invweights=None, weights_method='cov', wargs=(), optim_method='bfgs', optim_args=None)
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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
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