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.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.6 |
rolling linux/jammy R-4.5 | MRFA_0.6.tar.gz |
126.9 KiB |
0.6 |
rolling linux/noble R-4.5 | MRFA_0.6.tar.gz |
126.7 KiB |
0.6 |
rolling source/ R- | MRFA_0.6.tar.gz |
27.9 KiB |
0.6 |
latest linux/jammy R-4.5 | MRFA_0.6.tar.gz |
126.9 KiB |
0.6 |
latest linux/noble R-4.5 | MRFA_0.6.tar.gz |
126.7 KiB |
0.6 |
latest source/ R- | MRFA_0.6.tar.gz |
27.9 KiB |
0.6 |
2026-04-26 source/ R- | MRFA_0.6.tar.gz |
27.9 KiB |
0.6 |
2026-04-23 source/ R- | MRFA_0.6.tar.gz |
27.9 KiB |
0.6 |
2026-04-09 windows/windows R-4.5 | MRFA_0.6.zip |
129.2 KiB |
0.6 |
2025-04-20 source/ R- | MRFA_0.6.tar.gz |
27.9 KiB |