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Performs the MRFA approach proposed by Sung et al. (2020) <doi:10.1080/01621459.2019.1595630> to fit and predict nonlinear regression problems, particularly for large-scale and high-dimensional problems. The application includes deterministic or stochastic computer experiments, spatial datasets, and so on.
| Version: | 0.6 |
| Depends: | R (≥ 2.14.1) |
| Imports: | fields, glmnet, grplasso, methods, plyr, randtoolbox, foreach, stats, graphics, utils |
| Published: | 2023-11-10 |
| DOI: | 10.32614/CRAN.package.MRFA |
| Author: | Chih-Li Sung |
| Maintainer: | Chih-Li Sung <sungchih at msu.edu> |
| License: | GPL-2 | GPL-3 |
| NeedsCompilation: | no |
| CRAN checks: | MRFA results |
| Reference manual: | MRFA.pdf |
| Package source: | MRFA_0.6.tar.gz |
| Windows binaries: | r-devel: MRFA_0.6.zip, r-release: MRFA_0.6.zip, r-oldrel: MRFA_0.6.zip |
| macOS binaries: | r-release (arm64): MRFA_0.6.tgz, r-oldrel (arm64): MRFA_0.6.tgz, r-release (x86_64): MRFA_0.6.tgz, r-oldrel (x86_64): MRFA_0.6.tgz |
| Old sources: | MRFA archive |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.