Nature

Expectation-Maximization Algorithms in Statistical Inference

The expectation-maximization (EM) algorithm is a cornerstone technique for parameter estimation in statistical models that incorporate latent variables or incomplete data. By iteratively alternating ...
IEEE

Convergence of the Expectation-Maximization Algorithm Through Discrete-Time Lyapunov Stability Theory

Abstract: In this paper, we propose a dynamical systems perspective of the Expectation-Maximization (EM) algorithm. More precisely, we can analyze the EM algorithm as a nonlinear state-space dynamical ...
IEEE

Convergence of Expectation-Maximization Algorithm With Mixed-Integer Optimization

Abstract: The convergence of expectation-maximization (EM)-based algorithms typically requires continuity of the likelihood function with respect to all the unknown parameters (optimization variables) ...
Nature

A partition-ligation-combination-subdivision EM algorithm for haplotype inference with multiallelic markers: update of the SHEsis (http://analysis.bio-x.cn)

Haplotypic information in diploid organisms provides valuable information on human evolutionary history and plays an important role in identifying a candidate gene in the etiology of complex genetic ...