Bayesian Semiparametric Functional Mixed Models for Serially Correlated Functional Data, With Application to Glaucoma Data-Reference-Cited by-同舟云学术

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Bayesian Semiparametric Functional Mixed Models for Serially Correlated Functional Data, With Application to Glaucoma Data

Published:2018-08-15 Issue:526 Volume:114 Page:495-513
ISSN:0162-1459
Container-title:Journal of the American Statistical Association
language:en
Short-container-title:Journal of the American Statistical Association

Author:

Lee Wonyul¹,Miranda Michelle F.¹,Rausch Philip²,Baladandayuthapani Veerabhadran¹,Fazio Massimo³,Downs J. Crawford³,Morris Jeffrey S.¹

Affiliation:

1. Department of Biostatistics, University of Texas M.D. Anderson Cancer Center, Houston, TX

2. Institut für Psychologie, Humboldt-Universität zu Berlin, Berlin, Germany

3. Department of Ophthalmology, University of Alabama at Birmingham, Birmingham, AL

Funder

National Cancer Institute

National Eye Institute

National Science Foundation

Publisher

Informa UK Limited

Subject

Statistics, Probability and Uncertainty,Statistics and Probability

Link

https://www.tandfonline.com/doi/pdf/10.1080/01621459.2018.1476242

Reference56 articles.

1. Linguistic pitch analysis using functional principal component mixed effect models

2. Fitting Linear Mixed-Effects Models Usinglme4

3. A Bayesian approach to functional-based multilevel modeling of longitudinal data: applications to environmental epidemiology

4. Valid post-selection inference

5. Dirichlet–Laplace Priors for Optimal Shrinkage

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