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Journal of Computational and Graphical Statistics Volume 29, 2020 - Issue 4
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Monte Carlo and Approximation Methods

High-Dimensional Copula Variational Approximation Through Transformation

Michael Stanley SmithMelbourne Business School, University of Melbourne, Carlton, VIC, Australia; Correspondence[email protected]
,
Rubén Loaiza-MayaDepartment of Econometrics and Business Statistics, Monash University, Clayton, VIC, Australia;
&
David J. NottDepartment of Statistics and Applied Probability, National University of Singapore, Singapore
Pages 729-743 | Received 20 Feb 2019, Accepted 04 Mar 2020, Published online: 20 Apr 2020

Citations (11)

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Read on this site (3)

David Gunawan, Robert Kohn & David Nott. (2023) Flexible Variational Bayes Based on a Copula of a Mixture. Journal of Computational and Graphical Statistics 0:0, pages 1-16.
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Chong You, John T. Ormerod, Xiangyang Li, Cheng Heng Pang & Xiao-Hua Zhou. (2023) An Approximated Collapsed Variational Bayes Approach to Variable Selection in Linear Regression. Journal of Computational and Graphical Statistics 32:3, pages 782-792.
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Michael Stanley Smith & Rubén Loaiza-Maya. (2023) Implicit Copula Variational Inference. Journal of Computational and Graphical Statistics 32:3, pages 769-781.
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Articles from other publishers (8)

Matias Quiroz, David J. Nott & Robert Kohn. (2023) Gaussian Variational Approximations for High-dimensional State Space Models. Bayesian Analysis 18:3.
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Xuejun Yu, David J. Nott & Michael Stanley Smith. (2023) Variational Inference for Cutting Feedback in Misspecified Models. Statistical Science 38:3.
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Clara Hoffmann & Nadja Klein. (2023) Marginally calibrated response distributions for end-to-end learning in autonomous driving. The Annals of Applied Statistics 17:2.
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Vojtech Kejzlar & Tapabrata Maiti. (2022) Variational inference with vine copulas: an efficient approach for Bayesian computer model calibration. Statistics and Computing 33:1.
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Chandra R. Bhat & Aupal Mondal. (2022) A New Flexible Generalized Heterogeneous Data Model (GHDM) with an Application to Examine the Effect of High Density Neighborhood Living on Bicycling Frequency. Transportation Research Part B: Methodological 164, pages 244-266.
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Rubén Loaiza-Maya, Michael Stanley Smith, David J. Nott & Peter J. Danaher. (2022) Fast and accurate variational inference for models with many latent variables. Journal of Econometrics 230:2, pages 339-362.
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David Gunawan, Robert Kohn & David Nott. (2021) Variational Bayes approximation of factor stochastic volatility models. International Journal of Forecasting 37:4, pages 1355-1375.
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Hoang Nguyen, M. Concepción Ausín & Pedro Galeano. (2020) Variational inference for high dimensional structured factor copulas. Computational Statistics & Data Analysis 151, pages 107012.
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