Finite Mixture Models with Student t Distributions: an Applied Example-Reference-Cited by-同舟云学术

Finite Mixture Models with Student t Distributions: an Applied Example

Published:2020-04-18 Issue:6 Volume:21 Page:872-883
ISSN:1389-4986
Container-title:Prevention Science
language:en
Short-container-title:Prev Sci

Author:

Burgess-Hull Albert J.

Funder

National Institute on Drug Abuse

Publisher

Springer Science and Business Media LLC

Subject

Public Health, Environmental and Occupational Health

Link

https://link.springer.com/content/pdf/10.1007/s11121-020-01109-3.pdf

Reference49 articles.

1. Andrews, J. L., & McNicholas, P. D. (2012). Model-based clustering, classification, and discriminant analysis via mixtures of multivariate t-distributions. Statistics and Computing, 22, 1021–1029. https://doi.org/10.1007/s11222-011-9272-x.

2. Andrews, J. L., Wickins, J. R., Boers, N. M., & McNicholas, P. D. (2018). teigen: An R package for model-based clustering and classification via the multivariate t distribution. Journal of Statistical Software, 83, 1–32. https://doi.org/10.18637/jss.v083.i07.

3. Andrews, J. L., McNicholas, P. D., & Subedi, S. (2011). Model-based classification via mixtures of multivariate t-distributions. Computational Statistics & Data Analysis, 55, 520–529.

4. Asparouhov, T., & Muthén, B. (2016). Structural equation models and mixture models with continuous nonnormal skewed distributions. Structural Equation Modeling: A Multidisciplinary Journal, 23, 1–19.

5. Asparouhov, T., & Muthén, B. (2018). Variable-specific entropy contribution. Retrieved from http://www.statmodel.com/download/UnivariateEntropy.pdf.

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