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

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

Documentation:

Reference manual:MRFA.html ,MRFA.pdf

Downloads:

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

Linking:

Please use the canonical formhttps://CRAN.R-project.org/package=MRFAto link to this page.


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