cran
. See also theR-universe documentation.Package: RandomForestsGLS 0.1.5
RandomForestsGLS: Random Forests for Dependent Data
Fits non-linear regression models on dependant data with Generalised Least Square (GLS) based Random Forest (RF-GLS) detailed in Saha, Basu and Datta (2021) <doi:10.1080/01621459.2021.1950003>.
Authors:
RandomForestsGLS_0.1.5.tar.gz
RandomForestsGLS_0.1.5.tar.gz(r-4.5-noble)RandomForestsGLS_0.1.5.tar.gz(r-4.4-noble)
RandomForestsGLS_0.1.5.tgz(r-4.4-emscripten)RandomForestsGLS_0.1.5.tgz(r-4.3-emscripten)
RandomForestsGLS.pdf |RandomForestsGLS.html✨
RandomForestsGLS/json (API)
# Install 'RandomForestsGLS' in R: |
install.packages('RandomForestsGLS', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/arkajyotisaha/randomforestsgls/issues
Last updated 2 months agofrom:f6250910b5. Checks:OK: 1 WARNING: 1. Indexed: no.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Dec 02 2024 |
R-4.5-linux-x86_64 | WARNING | Dec 02 2024 |
Exports:RFGLS_estimate_spatialRFGLS_estimate_timeseriesRFGLS_predictRFGLS_predict_spatial
Dependencies:BRISCmatrixStatspbapplyrandomForestRANNRcppRcppArmadillordist
Readme and manuals
Help Manual
Help page | Topics |
---|---|
Function for estimation in spatial data with RF-GLS | RFGLS_estimate_spatial |
Function for estimation in time-series data with RF-GLS | RFGLS_estimate_timeseries |
Prediction of mean function with RF-GLS | RFGLS_predict |
Spatial response prediction at new location with RF-GLS | RFGLS_predict_spatial |