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. (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
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.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
Old sources: MRFA archive

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