Bayesian Shrinkage for Functional Network Models, With Applications to Longitudinal Item Response Data-Reference-Cited by-同舟云学术

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Bayesian Shrinkage for Functional Network Models, With Applications to Longitudinal Item Response Data

Published:2022-01-04 Issue: Volume: Page:1-18
ISSN:1061-8600
Container-title:Journal of Computational and Graphical Statistics
language:en
Short-container-title:Journal of Computational and Graphical Statistics

Author:

Park Jaewoo¹²,Jeon Yeseul¹,Shin Minsuk³,Jeon Minjeong⁴,Jin Ick Hoon¹²

Affiliation:

1. Department of Statistics and Data Science, Yonsei University, Seoul, South Korea

2. Department of Applied Statistics, Yonsei University, Seoul, South Korea

3. Department of Statistics, University of South Carolina, Columbia, SC

4. Graduate School of Education and Information Studies, University of California, Los Angeles, CA

Funder

Yonsei University Research Fund

National Research Foundation of Korea

NSF

Publisher

Informa UK Limited

Subject

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

Link

https://www.tandfonline.com/doi/pdf/10.1080/10618600.2021.1999823

Reference43 articles.

1. Bayesian computation for statistical models with intractable normalizing constants

2. Efficient Bayesian inference for exponential random graph models by correcting the pseudo-posterior distribution

3. Bayesian Model Selection for Exponential Random Graph Models via Adjusted Pseudolikelihoods

4. Bayesian inference for exponential random graph models

5. Caimo, A., and Friel, N. (2012), “Bergm: Bayesian Exponential Random Graphs in R,” arXiv:1201.2770.

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