Reports and tools

spatfGPs python and R packages (link to the website https://github.com/anfelopera/spatfGPs )

• spatfGP aims at building metamodels for cases where correlated spatial outputs (e.g. flood events) are driven by multiple functional inputs (e.g. hydro-meteorological conditions). Codes are based on the paper ``Multi-output Gaussian processes with functional data: A study on coastal flood hazard assessment'' (link to the paper: https://arxiv.org/abs/2007.14052)
• The repository provides Python and R codes based on the GPflow library and the kergp package (respectively)

• Betancourt, J., Bachoc, F., Klein, T., Gamboa, F. (2020). Technical Report: Ant Colony Based Model Selection for Functional-Input Gaussian Process Regression. Ref. D3.b (WP3.2), RISCOPE project. [Open access version]

• funGp R package [website]
  • Online releases: [GitHub], [CRAN].
  • User manual: Betancourt, J., Bachoc, F., Klein, T. (2020). R Package Manual: Gaussian Process Regression for Scalar and Functional Inputs with funGp - The in-depth tour. RISCOPE project.
  • Betancourt J., Bachoc F., Klein T., Idier D., Rohmer J., Deville Y. (2024) funGp: An R Package for Gaussian Process Regression with Scalar and Functional Inputs. Journal of Statistical Software, 109(5), 1–51. [POV]