Functional Concurrent Regression Mixture Models Using Spiked Ewens-Pitman Attraction Priors-Reference-Cited by-同舟云学术

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Functional Concurrent Regression Mixture Models Using Spiked Ewens-Pitman Attraction Priors

Published:2023-01-01 Issue:-1 Volume:-1 Page:
ISSN:1936-0975
Container-title:Bayesian Analysis
language:
Short-container-title:Bayesian Anal.

Author:

Liang Mingrui¹,Koslovsky Matthew D.²,Hébert Emily T.³,Businelle Michael S.⁴,Vannucci Marina¹

Affiliation:

1. Department of Statistics, Rice University, Houston, TX, USA

2. Department of Statistics, Colorado State University, Fort Collins, CO, USA

3. Department of Health Promotion and Behavioral Sciences, School of Public Health, University of Texas Health Science Center, Austin, TX 78701, USA

4. Department of Family and Preventive Medicine, College of Medicine, University of Oklahoma, Oklahoma City, OK 73104, USA

Publisher

Institute of Mathematical Statistics

Subject

Applied Mathematics,Statistics and Probability

Reference82 articles.

1. Meilă, M. (2007). “Comparing clusterings—an information based distance.” Journal of Multivariate Analysis, 98(5): 873–895.

2. Jacques, J. and Preda, C. (2014). “Functional Data Clustering: A Survey.” Advances in Data Analysis and Classification, 8(3): 231–255.

3. Bigelow, J. L. and Dunson, D. B. (2009). “Bayesian Semiparametric Joint Models for Functional Predictors.” Journal of the American Statistical Association, 104(485): 26–36.

4. Shin, M., Bhattacharya, A., and Johnson, V. E. (2020). “Functional horseshoe priors for subspace shrinkage.” Journal of the American Statistical Association, 115(532): 1784–1797.

5. Gertheiss, J., Maity, A., and Staicu, A.-M. (2013). “Variable selection in generalized functional linear models.” Stat, 2(1): 86–101.

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