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Jeffreys prior for mixture models [PDF]
, 2014 Mixture models may be a useful and flexible tool to describe data with a complicated structure, for instance characterized by multimodality or asymmetry. In a Bayesian setting, it is a well established fact that one need to be careful in using improper prior distributions, since the posterior distribution may not be proper.
GRAZIAN, CLARA, C. P. Robert
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A Novel Approach for Gaussian Mixture Model Clustering Based on Soft Computing Method
IEEE Access, 2021Maruf Gogebakan
exaly
The Bibliometric Analysis on Finite Mixture Model
SAGE Open, 2022Seuk Wai Phoong, Phoong Seuk Yen
exaly
Finite mixture models: McLachlan/finite mixture models
2000An up-to-date, comprehensive account of major issues in finite mixture modeling This volume provides an up-to-date account of the theory and applications of modeling via finite mixture distributions. With an emphasis on the applications of mixture models in both mainstream analysis and other areas such as unsupervised pattern recognition, speech ...
McLachlan, Geoffrey, Peel, David
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Assessing a mixture model for clustering with the integrated completed likelihood
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2000G Govaert
exaly