Bayesian Inference in Infinite Multivariate McDonald’s Beta Mixture Model

Author:

Forouzanfar DaryaORCID,Manouchehri NargesORCID,Bouguila NizarORCID

Publisher

Springer Nature Switzerland

Reference26 articles.

1. Amirkhani, M., Manouchehri, N., Bouguila, N.: A nonparametric bayesian framework for multivariate beta mixture models. In: 2021 IEEE 22nd International Conference on Information Reuse and Integration for Data Science (IRI), pp. 83–90 (2021)

2. Andrieu, C., De Freitas, N., Doucet, A., Jordan, M.I.: An introduction to mcmc for machine learning. Mach. Learn. 50(1/2), 5–43 (2003)

3. Anguita, D., Ghio, A., Oneto, L., Parra, X., Reyes-Ortiz, J.L.: A public domain dataset for human activity recognition using smartphones. In: 21st European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, ESANN. Bruges, Belgium, 24–26 April 2013https://www.kaggle.com/datasets/uciml/human-activity-recognition-with-smartphones

4. Aryal, G., Nadarajah, S.: Information matrix for beta distributions. Serdica Math. J. 30(4), 513–526 (2004)

5. Bishop, C.M.: Pattern Recognition and Machine Learning. Springer, 1 edn. (2006)

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