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ArvindRF  

Random Forest Regression with Arvind Distribution Error Model
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("ArvindRF", "1.0.0")



Attach the package and use:
library("ArvindRF")
Maintained by
Shikhar Tyagi
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2026-08-21
Latest Update: 2026-08-21
Description:
Implements Random Forest regression under the Arvind distribution error model. Provides core distribution functions (density, cumulative distribution, quantile, random generation, hazard, survival), parameter estimation via Expectation-Maximization (EM) and Markov Chain Monte Carlo (MCMC), non-parametric bootstrap confidence intervals (at 90%, 95%, and 99% levels), Highest Posterior Density (HPD) intervals, model evaluation metrics (estimated values, bias, mean squared error, risk value), homoscedastic prediction intervals, and goodness-of-fit diagnostic tests (Kolmogorov-Smirnov and Anderson-Darling tests, Akaike Information Criterion, and Bayesian Information Criterion). References: Breiman (2001) <doi:10.1023/A:1010933404324>; Wright and Ziegler (2017) <doi:10.18637/jss.v077.i01>.
How to cite:
Shikhar Tyagi (2026). ArvindRF: Random Forest Regression with Arvind Distribution Error Model. R package version 1.0.0, https://cran.r-project.org/web/packages/ArvindRF. Accessed 20 Oct. 2026.
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