An R Package AZIAD for Analyzing Zero-Inflated and Zero-Altered Data

TL;DR

AZIAD is an R package that offers extensive, accurate analysis tools for zero-inflated and zero-altered data, outperforming existing packages in model identification and parameter estimation.

Contribution

The paper introduces AZIAD, a comprehensive R package with new theoretical results, covering a broader class of models and providing improved estimation and model selection capabilities.

Findings

AZIAD provides more accurate parameter estimates.

AZIAD achieves higher power in model identification.

Simulation studies demonstrate AZIAD's advantages over existing packages.

Abstract

We introduce a newly developed R package AZIAD for analyzing zero-inflated or zero-altered data. Compared with existing R packages, AZIAD covers a much larger class of zero-inflated and hurdle models, including both discrete and continuous cases. It provides more accurate parameter estimates, along with the corresponding Fisher information matrix and confidence intervals. It achieves significantly larger power for model identification and selection. To facilitate the potential users, in this paper we provide detailed formulae and theoretical justifications for AZIAD, as well as new theoretical results on zero-inflated and zero-altered models. We use simulation studies to show the advantages of AZIAD functions over existing R packages and provide real data examples and executable R code to illustrate how to use our package for sparse data analysis and model selection.