Author ORCID Identifier
Date Available
12-15-2025
Year of Publication
2023
Degree Name
Doctor of Philosophy (PhD)
Document Type
Doctoral Dissertation
College
Arts and Sciences
Department/School/Program
Statistics
First Advisor
Dr. Derek S. Young
Abstract
Count data with excess zeros is common in many fields, such as ecology, healthcare, and insurance. Excess zeros data are often causing the inaccurate fit from the count models. While zero-inflated models have been developing for over two decades, one should also consider a more flexible model that can handle the excess zeros and further over- or under-dispersion. In this talk, we discuss zero-inflated discrete Weibull model and some novel computational contributions. The flexibility and competitiveness of the ZIDW model are illustrated by simulation studies and a real data analysis. We also investigate the performance of the proposed model through simulation studies, visualizations and diagnostics procedures. Finally, the computational tools developed have been included in an R package so that everyone can explore it in the future.
Digital Object Identifier (DOI)
https://doi.org/10.13023/etd.2023/472
Recommended Citation
Yeh, Peng, "Methodologies and Computational Tools for Zero-Inflated Discrete Weibull Models" (2023). Theses and Dissertations--Statistics. 73.
https://uknowledge.uky.edu/statistics_etds/73
