# Count Models Based on Weibull Interarrival Times

arXiv: https://arxiv.org/abs/1307.5759 · HTML: https://mlsanity.com/paper/1307.5759/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 22 Jul 2013.

## Built on by (most cited first, 4 of 4)

- [Active Learning For Repairable Hardware Systems With Partial Coverage](https://mlsanity.com/paper/2503.16315/) (2025)
- [Bayesian Semi-Parametric Spatial Dispersed Count Model for Precipitation Analysis](https://mlsanity.com/paper/2503.19117/) (2025)
- [Periodic evaluation of defined-contribution pension fund: A dynamic risk measure approach](https://mlsanity.com/paper/2508.05241/) (2025)
- [Scalable Amortized Variational Inference for Non-Poisson Buy-'Til-You-Die Models](https://mlsanity.com/paper/2608.19022/) (2026)

## 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.