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.">

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

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
License: GPL-2 | GPL-3
NeedsCompilation: no
CRAN checks: MRFA results

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