# An Expectation Maximization Framework for Yule-Simon Preferential Attachment Models

arXiv: https://arxiv.org/abs/1710.08511 · HTML: https://mlsanity.com/paper/1710.08511/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 23 Oct 2017.

## Built on by (most cited first, 1 of 1)

- [adSformers: Personalization from Short-Term Sequences and Diversity of Representations in Etsy Ads](https://mlsanity.com/paper/2302.01255/) (2023)

## Abstract (arXiv)

In this paper we develop an Expectation Maximization(EM) algorithm to estimate the parameter of a Yule-Simon distribution. The Yule-Simon distribution exhibits the "rich get richer" effect whereby an 80-20 type of rule tends to dominate. These distributions are ubiquitous in industrial settings. The EM algorithm presented provides both frequentist and Bayesian estimates of the λ parameter. By placing the estimation method within the EM framework we are able to derive Standard errors of the resulting estimate. Additionally, we prove convergence of the Yule-Simon EM algorithm and study the rate of convergence. An explicit, closed form solution for the rate of convergence of the algorithm is given. Applications including graph node degree distribution estimation are listed.