MRFA: Fitting and Predicting Large-Scale Nonlinear Regression Problems using Multi-Resolution Functional ANOVA (MRFA) Approach

Performs the MRFA approach proposed by Sung et al. (unpublished) to fit and predict nonlinear regression problems, particularly for large-scale and high-dimensional problems.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: 0.1
Depends: R (≥ 2.14.1)
Imports: fields, glmnet, grplasso, methods, plyr, randtoolbox, foreach, stats, graphics, utils
Published: 2017-07-14
Author: Chih-Li Sung
Maintainer: Chih-Li Sung <iamdfchile at>
License: GPL-2 | GPL-3
NeedsCompilation: no
CRAN checks: MRFA results


Reference manual: MRFA.pdf
Package source: MRFA_0.1.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X El Capitan binaries: r-release: MRFA_0.1.tgz
OS X Mavericks binaries: r-oldrel: MRFA_0.1.tgz


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