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bayesvalidrox 2.0.0 documentation
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  • USER GUIDE
    • Priors, input space and experimental design
    • Models
    • Training surrogate models
    • Active learning: iteratively expanding the training set
    • Postprocessing
    • Bayesian inference
    • Bayesian multi-model comparison
  • TUTORIAL
  • EXAMPLES
    • Analytical function
    • Beam
    • Borehole
    • Ishigami
    • Model comparison
    • OHagan-function
    • Pollution
  • API
    • bayesvalidrox
      • bayesvalidrox.bayes_inference
        • bayesvalidrox.bayes_inference.bayes_inference
          • bayesvalidrox.bayes_inference.bayes_inference.BayesInference
        • bayesvalidrox.bayes_inference.bayes_model_comparison
          • bayesvalidrox.bayes_inference.bayes_model_comparison.BayesModelComparison
        • bayesvalidrox.bayes_inference.discrepancy
          • bayesvalidrox.bayes_inference.discrepancy.Discrepancy
        • bayesvalidrox.bayes_inference.mcmc
          • bayesvalidrox.bayes_inference.mcmc.MCMC
        • bayesvalidrox.bayes_inference.post_sampler
          • bayesvalidrox.bayes_inference.post_sampler.PostSampler
        • bayesvalidrox.bayes_inference.rejection_sampler
          • bayesvalidrox.bayes_inference.rejection_sampler.RejectionSampler
      • bayesvalidrox.post_processing
        • bayesvalidrox.post_processing.post_processing
          • bayesvalidrox.post_processing.post_processing.PostProcessing
      • bayesvalidrox.pylink
        • bayesvalidrox.pylink.pylink
          • bayesvalidrox.pylink.pylink.within_range
          • bayesvalidrox.pylink.pylink.PyLinkForwardModel
      • bayesvalidrox.surrogate_models
        • bayesvalidrox.surrogate_models.apoly_construction
          • bayesvalidrox.surrogate_models.apoly_construction.apoly_construction
        • bayesvalidrox.surrogate_models.bayes_linear
          • bayesvalidrox.surrogate_models.bayes_linear.gamma_mean
          • bayesvalidrox.surrogate_models.bayes_linear.BayesianLinearRegression
          • bayesvalidrox.surrogate_models.bayes_linear.EBLinearRegression
          • bayesvalidrox.surrogate_models.bayes_linear.VBLinearRegression
        • bayesvalidrox.surrogate_models.engine
          • bayesvalidrox.surrogate_models.engine.Engine
        • bayesvalidrox.surrogate_models.eval_rec_rule
          • bayesvalidrox.surrogate_models.eval_rec_rule.eval_rec_rule
          • bayesvalidrox.surrogate_models.eval_rec_rule.eval_rec_rule_arbitrary
          • bayesvalidrox.surrogate_models.eval_rec_rule.eval_univ_basis
          • bayesvalidrox.surrogate_models.eval_rec_rule.poly_rec_coeffs
        • bayesvalidrox.surrogate_models.exp_designs
          • bayesvalidrox.surrogate_models.exp_designs.ExpDesigns
        • bayesvalidrox.surrogate_models.exploration
          • bayesvalidrox.surrogate_models.exploration.Exploration
        • bayesvalidrox.surrogate_models.gaussian_process_sklearn
          • bayesvalidrox.surrogate_models.gaussian_process_sklearn.GPESkl
          • bayesvalidrox.surrogate_models.gaussian_process_sklearn.MySklGPE
        • bayesvalidrox.surrogate_models.glexindex
          • bayesvalidrox.surrogate_models.glexindex.cross_truncate
          • bayesvalidrox.surrogate_models.glexindex.glexindex
        • bayesvalidrox.surrogate_models.input_space
          • bayesvalidrox.surrogate_models.input_space.InputSpace
        • bayesvalidrox.surrogate_models.inputs
          • bayesvalidrox.surrogate_models.inputs.Input
          • bayesvalidrox.surrogate_models.inputs.Marginal
        • bayesvalidrox.surrogate_models.meta_model
          • bayesvalidrox.surrogate_models.meta_model.transform_y
          • bayesvalidrox.surrogate_models.meta_model.MetaModel
        • bayesvalidrox.surrogate_models.orthogonal_matching_pursuit
          • bayesvalidrox.surrogate_models.orthogonal_matching_pursuit.corr
          • bayesvalidrox.surrogate_models.orthogonal_matching_pursuit.OrthogonalMatchingPursuit
        • bayesvalidrox.surrogate_models.pce_gpr
          • bayesvalidrox.surrogate_models.pce_gpr.PCEGPR
        • bayesvalidrox.surrogate_models.polynomial_chaos
          • bayesvalidrox.surrogate_models.polynomial_chaos.PCE
        • bayesvalidrox.surrogate_models.reg_fast_ard
          • bayesvalidrox.surrogate_models.reg_fast_ard.update_precisions
          • bayesvalidrox.surrogate_models.reg_fast_ard.RegressionFastARD
        • bayesvalidrox.surrogate_models.reg_fast_laplace
          • bayesvalidrox.surrogate_models.reg_fast_laplace.RegressionFastLaplace
        • bayesvalidrox.surrogate_models.sequential_design
          • bayesvalidrox.surrogate_models.sequential_design.SequentialDesign
        • bayesvalidrox.surrogate_models.supplementary
          • bayesvalidrox.surrogate_models.supplementary.check_ranges
          • bayesvalidrox.surrogate_models.supplementary.corr_loocv_error
          • bayesvalidrox.surrogate_models.supplementary.create_psi
          • bayesvalidrox.surrogate_models.supplementary.gelman_rubin
          • bayesvalidrox.surrogate_models.supplementary.hellinger_distance
          • bayesvalidrox.surrogate_models.supplementary.kernel_rbf
          • bayesvalidrox.surrogate_models.supplementary.root_mean_squared_error
          • bayesvalidrox.surrogate_models.supplementary.subdomain
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bayesvalidrox.pylink.pylinkΒΆ

Calls to the model and evaluations

Functions

within_range(out, minout, maxout)

Checks if all the values in out lie between minout and maxout

Classes

PyLinkForwardModel([link_type, name, ...])

A forward model binder

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