Zero-inflated Regression
Zero-Inflated Regression is a statistical modeling framework that belongs to the class of regression models designed for count data, distinguished by its incorporation of a dual-process mechanism that separately models structural zeros and sampling zeros to account for excess zero observations beyond what standard count distributions would predict.
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2017–2026
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Regression Models for Count Data in<i>R</i>
Achim Zeileis, Christian Kleiber, Simon Jackman · Journal of Statistical Software · 2008 · 2.4K citations · Full text
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University of North Carolina at Chapel Hill, United States
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Curtin University
Perth, Australia
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Universidade de São Paulo
São Paulo, Brazil
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University of North Carolina at Chapel Hill
Chapel Hill, United States
12 h-index
38 publications
1.7K citations

City University of Hong Kong
Hong Kong, Hong Kong
11 h-index
14 publications
1.3K citations
Arizona State University
Tempe, United States
10 h-index
13 publications
312 citations
Harvard University
Cambridge, United States
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10 publications
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Johns Hopkins University
Baltimore, United States
9 h-index
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978 citations

University of Hong Kong
Pok Fu Lam, Hong Kong
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24 publications
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CSDA · 12 publications · 1.1K citations
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