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RandomForestsGLS  

Random Forests for Dependent Data
View on CRAN: Click here


Download and install RandomForestsGLS package within the R console
Install from CRAN:
install.packages("RandomForestsGLS")

Install from Github:
library("remotes")
install_github("cran/RandomForestsGLS")

Install by package version:
library("remotes")
install_version("RandomForestsGLS", "0.1.5")



Attach the package and use:
library("RandomForestsGLS")
Maintained by
Arkajyoti Saha
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2021-01-08
Latest Update: 2022-04-28
Description:
Fits non-linear regression models on dependant data with Generalised Least Square (GLS) based Random Forest (RF-GLS) detailed in Saha, Basu and Datta (2020) .
How to cite:
Arkajyoti Saha (2021). RandomForestsGLS: Random Forests for Dependent Data. R package version 0.1.5, https://cran.r-project.org/web/packages/RandomForestsGLS. Accessed 03 Dec. 2024.
Previous versions and publish date:
0.1.0 (2021-01-08 11:50), 0.1.1 (2021-01-11 16:10), 0.1.2 (2021-01-31 01:50), 0.1.3 (2021-09-20 21:30), 0.1.4 (2022-04-28 15:30)
Other packages that cited RandomForestsGLS R package
View RandomForestsGLS citation profile
Other R packages that RandomForestsGLS depends, imports, suggests or enhances
Complete documentation for RandomForestsGLS
Functions, R codes and Examples using the RandomForestsGLS R package
Some associated functions: RFGLS_estimate_spatial . RFGLS_estimate_timeseries . RFGLS_predict . RFGLS_predict_spatial . 
Some associated R codes: RFGLS_estimate_spatial.R . RFGLS_estimate_timeseries.R . RFGLS_predict.R . RFGLS_predict_spatial.R . RFGLS_tree.R .  Full RandomForestsGLS package functions and examples
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