A variational expectation-maximization algorithm for temporal data clustering

DOI10.1016/j.csda.2016.05.007zbMath1466.62061OpenAlexW2399891531MaRDI QIDQ1658997

Gérard Govaert, Allou Samé, Patrice Aknin, Hani El Assaad

Publication date: 15 August 2018

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2016.05.007

zbMATH Keywords

EM algorithmclusteringKalman filtermaximum likelihoodmixture modelvariational approximationdynamic latent variable modeltemporal data clustering

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Classification and discrimination; cluster analysis (statistical aspects) (62H30)

Related Items (1)

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Uses Software

• fda (R)
• astsa
• StFinMetrics

Cites Work

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• A maximum likelihood methodology for clusterwise linear regression
• Block clustering with Bernoulli mixture models: comparison of different approaches
• Estimating the dimension of a model
• A mixture likelihood approach for generalized linear models
• An introduction to variational methods for graphical models
• Functional data analysis.
• Latent Class Analysis of Survey Error

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