Introduction | Example using RFplus | Load the example datasets | Prepare covariates and apply RFplus | Visualize the results | Example of displaying an interpolated layer | Note | Conclusion
Package: RFplus 1.5-4
Jonnathan Augusto Landi Bermeo
RFplus: Machine Learning for Merging Satellite and Ground Precipitation Data
A machine learning algorithm that merges satellite and ground precipitation data using Random Forest for spatial prediction, residual modeling for bias correction, and quantile mapping for adjustment, ensuring accurate estimates across temporal scales and regions.
Authors:
RFplus_1.5-4.tar.gz
RFplus_1.5-4.zip(r-4.7)RFplus_1.5-4.zip(r-4.6)RFplus_1.5-4.zip(r-4.5)
RFplus_1.5-4.tgz(r-4.6-any)RFplus_1.5-4.tgz(r-4.5-any)
RFplus_1.5-4.tar.gz(r-4.7-any)RFplus_1.5-4.tar.gz(r-4.6-any)
RFplus_1.5-4.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
RFplus/json (API)
| # Install 'RFplus' in R: |
| install.packages('RFplus', repos = c('https://jonnathan-landi.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/jonnathan-landi/rfplus/issues
Datasets:
- BD_Insitu - Precipitation Station Measurement Dataset
- Cords_Insitu - Precipitation Station Coordinates Dataset
Last updated from:ca74b82f52. Checks:7 NOTE, 2 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | NOTE | 253 | ||
| source / vignettes | OK | 221 | ||
| linux-release-x86_64 | NOTE | 232 | ||
| macos-release-arm64 | NOTE | 181 | ||
| macos-oldrel-arm64 | NOTE | 185 | ||
| windows-devel | NOTE | 186 | ||
| windows-release | NOTE | 183 | ||
| windows-oldrel | NOTE | 191 | ||
| wasm-release | OK | 164 |
Exports:RFplus
Dependencies:classclassIntcpp11data.tablee1071fitdistrplushydroGOFhydroTSMKernSmoothlatticeMASSMatrixpbapplyproxyqmaprandomForestRcpprlangsurvivalterratimechangextszoo
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Precipitation Station Measurement Dataset | BD_Insitu |
| Precipitation Station Coordinates Dataset | Cords_Insitu |
| Machine learning algorithm for fusing ground and satellite precipitation data. | RFplus RFplus.data.table RFplus.default |
