English

Computing the Dirichlet-Multinomial Log-Likelihood Function

Machine Learning 2020-07-24 v1 Artificial Intelligence Machine Learning

Abstract

Dirichlet-multinomial (DMN) distribution is commonly used to model over-dispersion in count data. Precise and fast numerical computation of the DMN log-likelihood function is important for performing statistical inference using this distribution, and remains a challenge. To address this, we use mathematical properties of the gamma function to derive a closed form expression for the DMN log-likelihood function. Compared to existing methods, calculation of the closed form has a lower computational complexity, hence is much faster without comprimising computational accuracy.

Keywords

Cite

@article{arxiv.2007.11967,
  title  = {Computing the Dirichlet-Multinomial Log-Likelihood Function},
  author = {Djallel Bouneffouf},
  journal= {arXiv preprint arXiv:2007.11967},
  year   = {2020}
}