LinearIVGMM.fititer()
statsmodels.sandbox.regression.gmm.LinearIVGMM.fititer
-
LinearIVGMM.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 : 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
© 2009–2012 Statsmodels Developers
© 2006–2008 Scipy Developers
© 2006 Jonathan E. Taylor
Licensed under the 3-clause BSD License.
http://www.statsmodels.org/stable/generated/statsmodels.sandbox.regression.gmm.LinearIVGMM.fititer.html