Package: UHM 0.3.0
UHM: Unified Zero-Inflated Hurdle Regression Models
Run a Gibbs sampler for hurdle models to analyze data showing an excess of zeros, which is common in zero-inflated count and semi-continuous models. The package includes the hurdle model under Gaussian, Gamma, inverse Gaussian, Weibull, Exponential, Beta, Poisson, negative binomial, logarithmic, Bell, generalized Poisson, and binomial distributional assumptions. The models described in Ganjali et al. (2024) <doi:...>.
Authors:
UHM_0.3.0.tar.gz
UHM_0.3.0.zip(r-4.5)UHM_0.3.0.zip(r-4.4)UHM_0.3.0.zip(r-4.3)
UHM_0.3.0.tgz(r-4.5-any)UHM_0.3.0.tgz(r-4.4-any)UHM_0.3.0.tgz(r-4.3-any)
UHM_0.3.0.tar.gz(r-4.5-noble)UHM_0.3.0.tar.gz(r-4.4-noble)
UHM_0.3.0.tgz(r-4.4-emscripten)UHM_0.3.0.tgz(r-4.3-emscripten)
UHM.pdf |UHM.html✨
UHM/json (API)
| # Install 'UHM' in R: |
| install.packages('UHM', repos = c('https://tbaghfalaki.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/tbaghfalaki/uhm/issues
- dataB - Simulated data from zero-inflated Beta regression model
- dataC - Simulated data from zero-inflated Gaussian regression model
- dataD - Simulated data from zero-inflated Poisson regression model
- dataI - Simulated data from zero-inflated exponential regression model
- dataP - Simulated data from zero-inflated exponential regression model
Last updated 5 months agofrom:96de13ea20. Checks:9 OK. Indexed: yes.
| Target | Result | Latest binary |
|---|---|---|
| Doc / Vignettes | OK | Mar 18 2025 |
| R-4.5-win | OK | Mar 18 2025 |
| R-4.5-mac | OK | Mar 18 2025 |
| R-4.5-linux | OK | Mar 18 2025 |
| R-4.4-win | OK | Mar 18 2025 |
| R-4.4-mac | OK | Mar 18 2025 |
| R-4.4-linux | OK | Mar 18 2025 |
| R-4.3-win | OK | Mar 18 2025 |
| R-4.3-mac | OK | Mar 18 2025 |
Exports:PredictionSummaryZIHRZIHR
