Count Models Based on Weibull Interarrival Times
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Abstract (arXiv)
In this paper, we introduce a generalized model for count data based upon an assumed Weibull interarrival process that nests the Poisson and negative binomial models as special cases. In addition, we demonstrate that this new Weibull count model can model both over and underdispersed count data, allow covariates to be introduced in a straightforward manner through the hazard function, and be computed in standard software.
Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). First posted on arXiv 22 Jul 2013.
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Citing papers per year: 2025: 3; 2026: 1.
4 papers.
- 2025Active Learning For Repairable Hardware Systems With Partial Coveragecited by 0
- 2025Bayesian Semi-Parametric Spatial Dispersed Count Model for Precipitation Analysiscited by 0
- 2025Periodic evaluation of defined-contribution pension fund: A dynamic risk measure approachcited by 0
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- 2026Scalable Amortized Variational Inference for Non-Poisson Buy-'Til-You-Die Models19 Aug 2026
- 2025Periodic evaluation of defined-contribution pension fund: A dynamic risk measure approach7 Aug 2025
- 2025Bayesian Semi-Parametric Spatial Dispersed Count Model for Precipitation Analysis24 Mar 2025
- 2025Active Learning For Repairable Hardware Systems With Partial Coverage20 Mar 2025