# Constructions for a bivariate beta distribution

arXiv: https://arxiv.org/abs/1406.5881 · HTML: https://mlsanity.com/paper/1406.5881/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 23 Jun 2014.

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

- [Uplift vs. predictive modeling: a theoretical analysis](https://mlsanity.com/paper/2309.12036/) (2023)
- [Do We Still Need Non-Maximum Suppression? Accurate Confidence Estimates and Implicit Duplication Modeling with IoU-Aware Calibration](https://mlsanity.com/paper/2309.03110/) (2023)
- [Flexible Bivariate Beta Mixture Model: A Probabilistic Approach for Clustering Complex Data Structures](https://mlsanity.com/paper/2502.19938/) (2025)
- [Identifying counterfactual probabilities using bivariate distributions and uplift modeling](https://mlsanity.com/paper/2512.08805/) (2025)

## Abstract (arXiv)

The beta distribution is a basic distribution serving several purposes. It is used to model data, and also, as a more flexible version of the uniform distribution, it serves as a prior distribution for a binomial probability. The bivariate beta distribution plays a similar role for two probabilities that have a bivariate binomial distribution. We provide a new multivariate distribution with beta marginal distributions, positive probability over the unit square, and correlations over the full range. We discuss its extension to three or more dimensions.