1Blurb:: 2Quasi-Newton optimization method 3Description:: 4This is a Newton method that expects a gradient and computes a 5low-rank approximation to the Hessian. Each of the Newton-based 6methods are automatically bound to the appropriate OPT++ algorithm 7based on the user constraint specification (unconstrained, 8bound-constrained, or generally-constrained). In the 9generally-constrained case, the Newton methods use a nonlinear 10interior-point approach to manage the constraints. 11 12See \ref topic-package_optpp for info related to all \c optpp methods. 13 14<b>Expected HDF5 Output</b> 15 16If Dakota was built with HDF5 support and run with the 17\ref environment-results_output-hdf5 keyword, this method 18writes the following results to HDF5: 19 20- \ref hdf5_results-best_params 21- \ref hdf5_results-best_obj_fncs (when \ref responses-objective_functions) are specified) 22- \ref hdf5_results-best_constraints 23- \ref hdf5_results-calibration (when \ref responses-calibration_terms are specified) 24 25Topics:: package_optpp, local_optimization_methods 26Examples:: 27Theory:: 28Faq:: 29