Performs the MRFA approach proposed by Sung et al. (2019+) <arXiv:1709.07064> 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: | 0.4 |
Depends: | R (≥ 2.14.1) |
Imports: | fields, glmnet, grplasso, methods, plyr, randtoolbox, foreach, stats, graphics, utils |
Published: | 2019-01-07 |
Author: | Chih-Li Sung |
Maintainer: | Chih-Li Sung <iamdfchile at gmail.com> |
License: | GPL-2 | GPL-3 |
NeedsCompilation: | no |
CRAN checks: | MRFA results |
Reference manual: | MRFA.pdf |
Package source: | MRFA_0.4.tar.gz |
Windows binaries: | r-devel: MRFA_0.4.zip, r-release: MRFA_0.4.zip, r-oldrel: MRFA_0.4.zip |
macOS binaries: | r-release: MRFA_0.4.tgz, r-oldrel: MRFA_0.4.tgz |
Old sources: | MRFA archive |
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