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Journal of Computational and Graphical Statistics Volume 30, 2021 - Issue 3
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Dimensionality Reduction, Regularization, and Variable Selection

Distributed Bayesian Inference in Linear Mixed-Effects Models

Sanvesh Srivastavaa Department of Statistics and Actuarial Science, The University of Iowa, Iowa City, IA; Correspondence[email protected]
ORCID Iconhttps://orcid.org/0000-0002-5483-9579View further author information
ORCID Icon &
Yixiang Xub Marketing Group, Haas School of Business, University of California, Berkeley, Berkeley, CAView further author information
Pages 594-611 | Received 30 Oct 2018, Accepted 21 Dec 2020, Published online: 08 Mar 2021

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Read on this site (1)

Jiayuan Zhou, Kshitij Khare & Sanvesh Srivastava. (2023) Asynchronous and Distributed Data Augmentation for Massive Data Settings. Journal of Computational and Graphical Statistics 32:3, pages 895-907.
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Articles from other publishers (4)

Yves Atchadé & Liwei Wang. (2023) A fast asynchronous Markov chain Monte Carlo sampler for sparse Bayesian inference. Journal of the Royal Statistical Society Series B: Statistical Methodology.
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Rajarshi Guhaniyogi, Cheng Li, Terrance Savitsky & Sanvesh Srivastava. (2023) Distributed Bayesian Inference in Massive Spatial Data. Statistical Science 38:2.
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Chunlei Wang & Sanvesh Srivastava. (2023) Divide-and-conquer Bayesian inference in hidden Markov models. Electronic Journal of Statistics 17:1.
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Nariankadu D. Shyamalkumar & Sanvesh Srivastava. (2022) An algorithm for distributed Bayesian inference. Stat 11:1.
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