A Variational Approximations-DIC Rubric for Parameter Estimation and Mixture Model Selection Within a Family Setting-Reference-Cited by-同舟云学术

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A Variational Approximations-DIC Rubric for Parameter Estimation and Mixture Model Selection Within a Family Setting

Published:2020-03-04 Issue:1 Volume:38 Page:89-108
ISSN:0176-4268
Container-title:Journal of Classification
language:en
Short-container-title:J Classif

Author:

Subedi Sanjeena,McNicholas Paul D.

Funder

NSERC: Discovery Grant

Canada Excellence Research Chairs, Government of Canada

NSERC: Collaborative Research and Development Grant

Publisher

Springer Science and Business Media LLC

Subject

Library and Information Sciences,Statistics, Probability and Uncertainty,Psychology (miscellaneous),Mathematics (miscellaneous)

Link

https://link.springer.com/content/pdf/10.1007/s00357-019-09351-3.pdf

Reference84 articles.

1. Aitken, A.C. (1926). A series formula for the roots of algebraic and transcendental equations. Proceedings of the Royal Society of Edinburgh, 45, 14–22.

2. Akaike, H. (1974). A new look at the statistical model identification. IEEE Transactions on Automatic Control, 19 (6), 716–723.

3. Banfield, J.D., & Raftery, A.E. (1993). Model-based Gaussian and non-Gaussian clustering. Biometrics, 49 (3), 803–821.

4. Bensmail, H., Celeux, G., Raftery, A.E., Robert, C.P. (1997). Inference in model-based cluster analysis. Statistics and Computing, 7, 1–10.

5. Biernacki, C., Celeux, G., Govaert, G. (2000). Assessing a mixture model for clustering with the integrated completed likelihood. IEEE Transactions on Pattern Analysis and Machine Intelligence, 22 (7), 719–725.

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