Index A | B | C | D | E | G | H | I | M | N | O | P | S | T | U | X A alpha (gpmpcontrib.optim.excursionset.ExcursionSetGridSearch attribute) AttrDict (class in gpmpcontrib.modelcontainer) B beta (gpmpcontrib.optim.excursionset.ExcursionSetGridSearch attribute) box_logprobability() (in module gpmpcontrib.samplingcriteria) box_misclassification_logprobability() (in module gpmpcontrib.samplingcriteria) box_misclassification_probability() (in module gpmpcontrib.samplingcriteria) box_probability() (in module gpmpcontrib.samplingcriteria) C computer_experiments_problem (gpmpcontrib.sequentialstrategy.SequentialStrategy attribute) ComputerExperiment (class in gpmpcontrib.computerexperiment) create_ackley_problem() (in module gpmpcontrib.test_problems) create_dixon_price_problem() (in module gpmpcontrib.test_problems) create_michalewicz_problem() (in module gpmpcontrib.test_problems) create_perm_problem() (in module gpmpcontrib.test_problems) create_rastrigin_problem() (in module gpmpcontrib.test_problems) create_rosenbrock_problem() (in module gpmpcontrib.test_problems) create_schwefel_problem() (in module gpmpcontrib.test_problems) create_shekel_problem() (in module gpmpcontrib.test_problems) create_trid_problem() (in module gpmpcontrib.test_problems) create_zakharov_problem() (in module gpmpcontrib.test_problems) current_estimate (gpmpcontrib.sequentialstrategy.SequentialStrategy attribute) D directed_hausdorff_distance() (in module gpmpcontrib.optim.pareto) distance() (in module gpmpcontrib.optim.pareto) dominated_area_2d() (in module gpmpcontrib.optim.pareto) E eval() (gpmpcontrib.computerexperiment.ComputerExperiment method) (gpmpcontrib.computerexperiment.StochasticComputerExperiment method) eval_constraints() (gpmpcontrib.computerexperiment.ComputerExperiment method) (gpmpcontrib.computerexperiment.StochasticComputerExperiment method) eval_objectives() (gpmpcontrib.computerexperiment.ComputerExperiment method) (gpmpcontrib.computerexperiment.StochasticComputerExperiment method) excursion_logprobability() (in module gpmpcontrib.samplingcriteria) excursion_misclassification_probability() (in module gpmpcontrib.samplingcriteria) excursion_probability() (in module gpmpcontrib.samplingcriteria) ExcursionSetGridSearch (class in gpmpcontrib.optim.excursionset) exec_times (gpmpcontrib.sequentialstrategy.SequentialStrategy attribute) expected_improvement() (in module gpmpcontrib.samplingcriteria) ExpectedImprovementGridSearch (class in gpmpcontrib.optim.expectedimprovement) ExpectedImprovementSMC (class in gpmpcontrib.optim.expectedimprovement) G g (gpmpcontrib.optim.excursionset.ExcursionSetGridSearch attribute) get_constraint_bounds() (gpmpcontrib.computerexperiment.ComputerExperiment method) get_model_params() (gpmpcontrib.sequentialstrategy.SequentialStrategy method) get_model_state() (gpmpcontrib.sequentialstrategy.SequentialStrategy method) get_output_bounds() (gpmpcontrib.computerexperiment.ComputerExperiment method) get_output_types() (gpmpcontrib.computerexperiment.ComputerExperiment method) get_simulated_noise_variances() (gpmpcontrib.computerexperiment.StochasticComputerExperiment method) gpmpcontrib module gpmpcontrib.computerexperiment module gpmpcontrib.modelcontainer module gpmpcontrib.optim.excursionset module gpmpcontrib.optim.expectedimprovement module gpmpcontrib.optim.pareto module gpmpcontrib.optim.setinversion module gpmpcontrib.plot.visualization module gpmpcontrib.samplingcriteria module gpmpcontrib.sequentialprediction module gpmpcontrib.sequentialstrategy module H hausdorff_distance() (in module gpmpcontrib.optim.pareto) history (gpmpcontrib.sequentialstrategy.SequentialStrategy attribute) I init_smc() (gpmpcontrib.sequentialstrategy.SequentialStrategyBSS method) (gpmpcontrib.sequentialstrategy.SequentialStrategySMC method) M maximize_criterion (gpmpcontrib.sequentialstrategy.SequentialStrategy attribute) mean_linpred_constant() (in module gpmpcontrib.modelcontainer) mean_linpred_linear() (in module gpmpcontrib.modelcontainer) module gpmpcontrib gpmpcontrib.computerexperiment gpmpcontrib.modelcontainer gpmpcontrib.optim.excursionset gpmpcontrib.optim.expectedimprovement gpmpcontrib.optim.pareto gpmpcontrib.optim.setinversion gpmpcontrib.plot.visualization gpmpcontrib.samplingcriteria gpmpcontrib.sequentialprediction gpmpcontrib.sequentialstrategy N n_iter (gpmpcontrib.sequentialstrategy.SequentialStrategy attribute) normalize_input (gpmpcontrib.computerexperiment.ComputerExperiment property) nt (gpmpcontrib.sequentialstrategy.SequentialStrategy attribute) O options (gpmpcontrib.sequentialstrategy.SequentialStrategy attribute) P pareto_filter() (in module gpmpcontrib.optim.pareto) pareto_gt() (in module gpmpcontrib.optim.pareto) pareto_lt() (in module gpmpcontrib.optim.pareto) pareto_points() (in module gpmpcontrib.optim.pareto) pareto_points_unsorted() (in module gpmpcontrib.optim.pareto) plot_1d() (in module gpmpcontrib.plot.visualization) plot_pareto() (in module gpmpcontrib.optim.pareto) plotmatrix() (in module gpmpcontrib.plot.visualization) S sampling_criterion() (gpmpcontrib.optim.excursionset.ExcursionSetGridSearch method) (gpmpcontrib.optim.expectedimprovement.ExpectedImprovementGridSearch method) (gpmpcontrib.optim.expectedimprovement.ExpectedImprovementSMC method) (gpmpcontrib.optim.setinversion.SetInversionGridSearch method) sampling_criterion_values (gpmpcontrib.sequentialstrategy.SequentialStrategy attribute) SelectionCriterionBuildContext (class in gpmpcontrib.modelcontainer) SequentialStrategy (class in gpmpcontrib.sequentialstrategy) SequentialStrategyBSS (class in gpmpcontrib.sequentialstrategy) SequentialStrategyGridSearch (class in gpmpcontrib.sequentialstrategy) SequentialStrategySMC (class in gpmpcontrib.sequentialstrategy) SetInversionGridSearch (class in gpmpcontrib.optim.setinversion) show_loo_errors() (in module gpmpcontrib.plot.visualization) show_truth_vs_prediction() (in module gpmpcontrib.plot.visualization) simulated_noise_variance (gpmpcontrib.computerexperiment.StochasticComputerExperiment property) smc (gpmpcontrib.sequentialstrategy.SequentialStrategyBSS attribute) (gpmpcontrib.sequentialstrategy.SequentialStrategySMC attribute) smc_log_density() (gpmpcontrib.optim.expectedimprovement.ExpectedImprovementSMC method) smc_log_density_param (gpmpcontrib.sequentialstrategy.SequentialStrategyBSS attribute) (gpmpcontrib.sequentialstrategy.SequentialStrategySMC attribute) smc_log_density_param_initial (gpmpcontrib.sequentialstrategy.SequentialStrategySMC attribute) StochasticComputerExperiment (class in gpmpcontrib.computerexperiment) symmdiff_area_2d() (in module gpmpcontrib.optim.pareto) T tau (gpmpcontrib.optim.excursionset.ExcursionSetGridSearch attribute) test_pareto() (in module gpmpcontrib.optim.pareto) U update_current_estimate() (gpmpcontrib.optim.excursionset.ExcursionSetGridSearch method) (gpmpcontrib.optim.expectedimprovement.ExpectedImprovementGridSearch method) (gpmpcontrib.optim.expectedimprovement.ExpectedImprovementSMC method) (gpmpcontrib.optim.setinversion.SetInversionGridSearch method) update_search_space() (gpmpcontrib.sequentialstrategy.SequentialStrategyBSS method) (gpmpcontrib.sequentialstrategy.SequentialStrategySMC method) update_smc_target_log_density_param() (gpmpcontrib.optim.expectedimprovement.ExpectedImprovementSMC method) X xt (gpmpcontrib.sequentialstrategy.SequentialStrategy attribute)