Beyond the EM algorithm: constrained optimization methods for latent class model

DOI10.1080/03610918.2020.1764034OpenAlexW3104347455MaRDI QIDQ5042122

Alvin Lim, Lanshan Han, Hao Chen

Publication date: 18 October 2022

Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1901.02928

zbMATH Keywords

EM algorithmconstrained optimizationfinite mixture modelquasi-Newton's methodlatent class modelquadratic programing

Mathematics Subject Classification ID

Statistics (62-XX)

Uses Software

• BayesLCA

Cites Work

• On the convergence properties of the EM algorithm
• A globally convergent method for nonlinear programming
• Representations of quasi-Newton matrices and their use in limited memory methods
• Nonmonotone Spectral Projected Gradient Methods on Convex Sets
• Randomized Quasi-Newton Updates Are Linearly Convergent Matrix Inversion Algorithms
• Constructing Confidence Sets Using Rank Statistics
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