Acceleration of the EM and ECM algorithms using the Aitken \(\delta^2\) method for log-linear models with partially classified data

DOI10.1016/J.SPL.2008.01.102zbMath1146.62053OpenAlexW2034375348MaRDI QIDQ951173

Zhi Geng, Masahiro Kuroda, Michio Sakakihara

Publication date: 30 October 2008

Published in: Statistics \& Probability Letters (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.spl.2008.01.102

Mathematics Subject Classification ID

Generalized linear models (logistic models) (62J12)

Related Items (2)

Acceleration of expectation-maximization algorithm for length-biased right-censored data ⋮ Acceleration of the EM algorithm using the Vector Aitken method and its Steffensen form

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• The EM algorithm for graphical association models with missing data
• Analysis of multivariate categorical data with misclassification errors by triple sampling schemes
• Extrapolation methods theory and practice
• Maximum likelihood estimation via the ECM algorithm: A general framework
• Inference and missing data

This page was built for publication: Acceleration of the EM and ECM algorithms using the Aitken \(\delta^2\) method for log-linear models with partially classified data