About
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Introduction
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PyApprox provides flexible and efficient tools for credible data-informed decision making. PyApprox implements methods addressing various issues surrounding high-dimensional parameter spaces and limited evaluations of expensive simulation models with the goal of facilitating simulation-aided knowledge discovery, prediction and design. Methods are available for: low-rank tensor-decomposition; Gaussian processes; polynomial chaos expansions; sparse-grids; risk-adverse regression; compressed sensing; Bayesian inference; push-forward based inference; optimal design of computer experiments for interpolation regression and compressed sensing; and risk-adverse optimal experimental design.

Team
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PyApprox was written and developed by Dr. John D. Jakeman. John is a Principle Member of Technical Staff at Sandia National Laboratories, Albuquerque USA. A list of his publications can be found at `Google Scholar <https://scholar.google.com/citations?hl=en&user=tupqTFgAAAAJ>`_.

Citing PyApprox
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If you use in a research publication, citations to the following paper would be appreciated:


  `PyApprox: A software package for sensitivity analysis, Bayesian inference, optimal experimental design, and multi-fidelity uncertainty quantification and surrogate modeling
  <https://doi.org/10.1016/j.envsoft.2023.105825>`_, J.D. Jakeman, Environmental Modelling & Software, 170, pp. 105825, 2023.

  Bibtex entry::

    @article{PyApprox,
     title = {PyApprox: A software package for sensitivity analysis, Bayesian inference, optimal experimental design, and multi-fidelity uncertainty quantification and surrogate modeling},
     journal = {Environmental Modelling \& Software},
     volume = {170},
     pages = {105825},
     year = {2023},
     url = {https://doi.org/10.1016/j.envsoft.2023.105825},
     author = {J.D. Jakeman}
    }

Acknowledgments
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Sandia National Laboratories is a multi-mission laboratory managed and operated by National Technology and Engineering Solutions of Sandia, LLC., a wholly owned subsidiary of Honeywell International, Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA-0003525. The views expressed in the article do not necessarily represent the views of the U.S. Department of Energy or the United States Government.