Event Count Models is a statistical modeling framework that belongs to the class of count data models and is specifically designed to analyze the frequency of discrete events occurring within a fixed observational unit by distinguishing itself through its focus on non-negative integer outcomes generated from well-defined counting processes.
319
Publications
27.4K
Citations
706
Authors
391
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Publications per year
2017–2026
64
Variants
Event Count Modeling
Parents
Publications
319
Regression Analysis of Count Data
John J. Peterson, A. Colin Cameron, Pravin K. Trivedi · Technometrics · 1999 · 697 citations
Comparison and evaluation of statistical error models for scRNA-seq
Saket Choudhary · Genome biology · 2022 · 665 citations · Full text
1–5 of 319
Authors
706
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1–5 of 706
Institutions
391
Purdue University West Lafayette
West Lafayette, United States
6 h-index
11 publications
2.6K citations
Harvard University Press
Cambridge, United States
6 h-index
8 publications
443 citations
University of South Carolina
Columbia, United States
6 h-index
10 publications
626 citations
Johns Hopkins University
Baltimore, United States
5 h-index
8 publications
826 citations
Texas A&M University
College Station, United States
5 h-index
12 publications
578 citations
Cornell University
Ithaca, United States
4 h-index
8 publications
435 citations
The Ohio State University
Columbus, United States
4 h-index
5 publications
579 citations
University of Iowa
Iowa City, United States
4 h-index
3 publications
165 citations
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- Accident Analysis & Prevention
10 publications · 1.8K citations
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- Technometrics
8 publications · 1.8K citations
8
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- Journal of the American Statistical Association
7 publications · 622 citations
7
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- Computational Statistics & Data Analysis
CSDA · 7 publications · 454 citations
7
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- American Journal of Political Science
AJPS · 6 publications · 646 citations
6
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