Package: PowerXgammaRF Type: Package Title: Random Forest Regression with Power Xgamma Distribution Error Model Version: 1.0.0 Authors@R: c( person("Shikhar", "Tyagi", email = "shikhar1093tyagi@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0003-1606-0844")), person("Aruna", "Rajballie", email = "aruna.rajballie@utt.edu.tt", role = "aut"), person("Vrijesh", "Tripathi", email = "vrijesh.tripathi@uwi.edu", role = "aut") ) 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) ; Wright and Ziegler (2017) ; Heidelberger and Welch (1983) ; Sen et al. (2016) . License: GPL (>= 3) Encoding: UTF-8 RoxygenNote: 7.3.3 Depends: R (>= 4.0.0) Imports: ranger, coda, goftest, stats, graphics Suggests: testthat (>= 3.0.0) Config/testthat/edition: 3 Language: en-US NeedsCompilation: no Packaged: 2026-09-21 09:42:00 UTC; root Author: Shikhar Tyagi [aut, cre] (ORCID: ), Aruna Rajballie [aut], Vrijesh Tripathi [aut] Maintainer: Shikhar Tyagi Repository: https://shikhartyagi.r-universe.dev Date/Publication: 2026-08-21 13:20:24 UTC RemoteUrl: https://github.com/cran/PowerXgammaRF RemoteRef: HEAD RemoteSha: 2408dd94d4fe42c28ce882e8db00f3ff4bdde390