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PowerXgammaRF  

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


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

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

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



Attach the package and use:
library("PowerXgammaRF")
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 Power Xgamma 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, Heidelberger and Welch's MCMC convergence diagnostic, convergence probability, 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: Tyagi et al. (2022, Int. J. Stat. Reliab. Eng., 9(1), 51-60); Breiman (2001) <doi:10.1023/A:1010933404324>; Wright and Ziegler (2017) <doi:10.18637/jss.v077.i01>; Heidelberger and Welch (1983) <doi:10.1287/opre.31.6.1109>; Sen et al. (2016) <doi:10.22237/jmasm/1462076400>.
How to cite:
Shikhar Tyagi (2026). PowerXgammaRF: Random Forest Regression with Power Xgamma Distribution Error Model. R package version 1.0.0, https://cran.r-project.org/web/packages/PowerXgammaRF. Accessed 24 Oct. 2026.
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Complete documentation for PowerXgammaRF
Functions, R codes and Examples using the PowerXgammaRF R package
Full PowerXgammaRF package functions and examples
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