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Construction and smart selection of Gaussian process models for analysis of computer experiments with emphasis on treatment of functional inputs that are regularly sampled. This package offers: (i) flexible modeling of functional-input regression problems through the fairly general Gaussian process model; (ii) built-in dimension reduction for functional inputs; (iii) heuristic optimization of the structural parameters of the model (e.g., active inputs, kernel function, type of distance). An in-depth tutorial in the use of funGp is provided in Betancourt et al. (2024) <doi:10.18637/jss.v109.i05> and Metamodeling background is provided in Betancourt et al. (2020) <doi:10.1016/j.ress.2020.106870>. The algorithm for structural parameter optimization is described in <https://hal.science/hal-02532713>.
| Version: | 1.0.0 |
| Depends: | R (≥ 3.5.0) |
| Imports: | methods, foreach, knitr, scales, microbenchmark, doFuture, doRNG, future, progressr |
| Published: | 2024-05-10 |
| DOI: | 10.32614/CRAN.package.funGp |
| Author: | Jose Betancourt [cre, aut], François Bachoc [aut], Thierry Klein [aut], Jeremy Rohmer [aut], Yves Deville [ctb], Deborah Idier [ctb] |
| Maintainer: | Jose Betancourt <fungp.rpack at gmail.com> |
| BugReports: | https://github.com/djbetancourt-gh/funGp/issues |
| License: | GPL-3 |
| URL: | https://djbetancourt-gh.github.io/funGp/, https://github.com/djbetancourt-gh/funGp |
| NeedsCompilation: | no |
| Citation: | funGp citation info |
| Materials: | README NEWS |
| CRAN checks: | funGp results |
| Reference manual: | funGp.pdf |
| Package source: | funGp_1.0.0.tar.gz |
| Windows binaries: | r-devel: funGp_1.0.0.zip, r-release: funGp_1.0.0.zip, r-oldrel: funGp_1.0.0.zip |
| macOS binaries: | r-release (arm64): funGp_1.0.0.tgz, r-oldrel (arm64): funGp_1.0.0.tgz, r-release (x86_64): funGp_1.0.0.tgz, r-oldrel (x86_64): funGp_1.0.0.tgz |
| Old sources: | funGp archive |
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These binaries (installable software) and packages are in development.
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