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PowerXgammaRF

1.0.0Package record

Random Forest Regression with Power Xgamma Distribution Error Model

0packages depend
484downloads / year
76.0%test coverage
13/13flavors OK

Overview

About

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.

Install

Health

CRAN checks
13OK
Slowest check: 1.0 min · r-oldrel-windows-x86_64
Status changes
  • OK13 OKNow
  • OK7 OK2026-08-22
Advisories

none known

Documentation

In release 1.0.0
READMENoVignettesNoNEWSNoCitation fileNoWebsitenot declared in DESCRIPTION
Description cites a JSS article
Help pages
6
Examples that run
100%6 run in a plain check
Exported functions with examples
100%
Documented parameters
91%
Return-value docs
100%
Help pages citing references
100%

Downloads

484
CRAN downloads in the past year
Rank #24,321 · ~1/day · ~40/mo
Daily download trend is not available in this view yet.
22530 days
48490 days
4841 year
Compare downloads with other packages →
Also on14 r2u2 autocran

Dependencies

Declared dependencies
4 external dependencies (excludes base and recommended)

Installing PowerXgammaRF adds 5 packages (4 with compiled code, 3.8 MB of source tarballs). Heaviest: Rcpp 1.8 MB, RcppEigen 1.7 MB, ranger 175 KB.

Depends (1)
R >= 4.0.0
Imports (5)
rangercodagofteststatsgraphics
LinkingTo (0)
none
Suggests (1)
Enhances (0)
none
Reverse dependencies
0direct
0indirect

Nothing depends on this yet.

People & History

People (3)
Author, Maintainer since 1.0.0 (2026)
Releases (1)
  • 1.0.0Latest
    2026-08-21 · current release
  • R
    R 4.6.0 released · 2026-04-24

Package metadata

First published
2026-08-21
Total releases
1 / 1 yrs
License
GPL (>= 3) OSI
Minimum R
≥ 4.0.0
Download size
20 KB
Appears in task views

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("PowerXgammaRF")
Tyagi, S., Rajballie, A., & Tripathi, V. (2026). PowerXgammaRF: Random Forest Regression with Power Xgamma Distribution Error Model (Version 1.0.0) [Computer software]. https://doi.org/10.32614/CRAN.package.PowerXgammaRF

This package has no citation file, so citation() returns this entry built from DESCRIPTION.

Cite the R Observatory

For a number measured here: a download total, a coverage figure, an archival date.

APA

Balamuta, J. J. (2026). R Observatory: Metrics for PowerXgammaRF version 1.0.0 [Data set]. HJJB, LLC. Data release v2026-10-18. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-18, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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