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.

Installation

To acquire the latest development version of UHM, you may utilize the following code snippet to install it directly from GitHub:

  # install.packages("devtools")
  devtools::install_github("tbaghfalaki/UHM")

This will seamlessly fetch and install the most up-to-date version of UHM for your use.

The package is now accessible on R CRAN as well! [https://cran.r-project.org/web/packages/UHM/index.html]

install.packages("UHM")

Hurdle models

Descriptions of various hurdle models are presented here

Example Usage

This analysis is presented here

Analysis of the Number of infected blood cells data and the Auto-insurance claim data is presented here

Reference

Ganjali, M., Baghfalaki, T. & Balakrishnan, N. (2024). A Unified Bayesian approach for Modeling Zero-Inflated count and continuous outcomes. Revised.