Count Data Forecasting
Count Data Forecasting is a predictive modeling methodology that specifically addresses the estimation of future count-valued outcomes—non-negative integers arising from discrete events—by leveraging statistical or machine learning models tailored to the distributional properties of count data, such as overdispersion, excess zeros, and non-negative support.
30
Publications
1.1K
Citations
83
Authors
65
Institutions
Publications per year
2017–2026
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65

Indian Statistical Institute
Kolkata, India
2 h-index
4 publications
62 citations

University of Wisconsin–Milwaukee
Milwaukee, United States
2 h-index
2 publications
34 citations
University of Würzburg
Würzburg, Germany
2 h-index
2 publications
34 citations

Helmut Schmidt University
Hamburg, Germany
2 h-index
6 publications
102 citations
Amity University
Dubai, United Arab Emirates
1 h-index
1 publications
51 citations
Research Institute of Forestry
Beijing, China
1 h-index
1 publications
31 citations

Providence College
Providence, United States
1 h-index
1 publications
17 citations
Bucknell University
Lewisburg, United States
1 h-index
1 publications
103 citations
1–8 of 65
3 publications · 39 citations
3
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2 publications · 263 citations
2
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2 publications · 56 citations
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TRR · 2 publications · 133 citations
2
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1 publications · 113 citations
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1–5