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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.
Getting started
Browse package contents
Package details |
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| Author | Jonnathan Augusto Landi Bermeo [aut, cre, cph] (<https://orcid.org/0009-0003-3162-6647>), Alex Avilés [aut] (<https://orcid.org/0000-0001-9278-5738>), Darío Zhiña [aut] (<https://orcid.org/0000-0001-9556-4025>), Marco Mogro [aut] (<https://orcid.org/0009-0007-1802-9417>), Anthony Guamán [aut] (<https://orcid.org/0009-0005-0204-7536>) |
| Maintainer | Jonnathan Augusto Landi Bermeo <jonnathan.landi@outlook.com> |
| License | GPL (>= 3) |
| Version | 1.5-4 |
| URL | https://github.com/Jonnathan-Landi/RFplus |
| Package repository | View on CRAN |
| Installation |
Install the latest version of this package by entering the following in R:
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