Optimizing information using the EM algorithm in item response theory

DOI10.1007/s10479-012-1204-4zbMathNoneOpenAlexW1978154058MaRDI QIDQ363608

Alexander Weissman

Publication date: 3 September 2013

Published in: Annals of Operations Research (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10479-012-1204-4

zbMATH Keywords

item response theoryrelative entropyEM algorithmmodel selectioninformation theoryKullback-Leibler divergencestatistical estimationlatent trait theorymarginal maximum likelihood

Mathematics Subject Classification ID

Statistics (62-XX)

Cites Work

• On the convergence properties of the EM algorithm
• Model selection and Akaike's information criterion (AIC): The general theory and its analytical extensions
• Statistical estimation from an optimization viewpoint
• Global convergence of the EM algorithm for unconstrained latent variable models with categorical indicators
• A tutorial on the cross-entropy method
• The EM Algorithm and Extensions, 2E
• Item Response Theory
• Elements of Information Theory
• On Information and Sufficiency
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