Data transforming augmentation for heteroscedastic models-Reference-Cited by-同舟云学术

Data transforming augmentation for heteroscedastic models

Published:2020-02-07 Issue:3 Volume:29 Page:659-667
ISSN:1061-8600
Container-title:Journal of Computational and Graphical Statistics
language:en
Short-container-title:Journal of Computational and Graphical Statistics

Author:

Tak Hyungsuk¹^ORCID,You Kisung²,Ghosh Sujit K.³^ORCID,Su Bingyue²,Kelly Joseph⁴

Affiliation:

1. Departments of Statistics, Astronomy and Astrophysics, Institute for Computational and Data Sciences, Pennsylvania State University, University Park, PA

2. Department of Applied and Computational Mathematical and Statistics University of Notre Dame, Notre Dame, IN

3. Department of Statistics, North Carolina State University, Raleigh, NC

4. Google LLC, Mountain View, CA

Publisher

Informa UK Limited

Subject

Statistics, Probability and Uncertainty,Discrete Mathematics and Combinatorics,Statistics and Probability

Link

https://www.tandfonline.com/doi/pdf/10.1080/10618600.2019.1704295

Reference28 articles.

1. A prior for the variance in hierarchical models

2. Maximum Likelihood from Incomplete Data Via theEMAlgorithm

3. Data Analysis Using Stein's Estimator and its Generalizations

4. Bayesian Inference for the Beta-Binomial Distribution via Polynomial Expansions

5. Inference for multivariate normal hierarchical models

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