Random Forest Regression with Modified Topp-Leone Error Model
Overview
Implements Random Forest regression under the Modified Topp-Leone (MTL) distribution error model. Provides core distribution functions (density, cumulative distribution, exact closed-form quantile, random generation, hazard, and survival), parameter estimation via closed-form Expectation-Maximization/Maximum Likelihood (EM/MLE) and Bayesian Markov Chain Monte Carlo (MCMC), non-parametric bootstrap confidence intervals (at 90%, 95%, and 99% levels), Highest Posterior Density (HPD) intervals, Heidelberger and Welch MCMC convergence diagnostics, 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; Singh, Tyagi, Singh, and Tyagi (2025) https://statassoc.or.th; Topp and Leone (1955) doi:10.1080/01621459.1955.10501259; Wright and Ziegler (2017) doi:10.18637/jss.v077.i01; Plummer, Best, Cowles, and Vines (2006) https://CRAN.R-project.org/package=coda; Heidelberger and Welch (1983) doi:10.1287/opre.31.6.1109.
Install
Health
- OK13 OK2026-09-08
- ERROR12 OK, 1 ERROR2026-09-07
- OK7 OK2026-08-22
Documentation
- Help pages
- 7
- Examples that run
- 100%7 run in a plain check
- Exported functions with examples
- 100%
- Documented parameters
- 90%
- Return-value docs
- 100%
- Help pages citing references
- 0%
Downloads
Dependencies
Code & Tests
People & History
- 1.0.0Latest2026-08-21 · current release
- RR 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
- 16 KB
Cite
Cite this package
Run in R for the authors' preferred citation:
citation("MTLRF")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.
From data release v2026-10-21, which the citation names so these numbers can be found later. More on citing and the projects behind them.