Loss-Based Variational Bayes Prediction

IF 1.4 2区数学 Q2 STATISTICS & PROBABILITY

Journal of Computational and Graphical Statistics Pub Date : 2024-04-16 DOI:10.1080/10618600.2024.2341899

David T. Frazier, Rubén Loaiza-Maya, Gael M. Martin, Bonsoo Koo

引用次数: 0

Abstract

We propose a new approach to Bayesian prediction that caters for models with a large number of parameters and is robust to model misspecification. Given a class of high-dimensional (but parametric)...

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基于损失的变异贝叶斯预测

我们提出了一种新的贝叶斯预测方法，这种方法能满足具有大量参数的模型的要求，并对模型的错误规范具有鲁棒性。给定一类高维（但参数化）...

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来源期刊

Journal of Computational and Graphical Statistics 数学-统计学与概率论

CiteScore

3.50

自引率

8.30%

发文量

153

审稿时长

>12 weeks

期刊介绍： The Journal of Computational and Graphical Statistics (JCGS) presents the very latest techniques on improving and extending the use of computational and graphical methods in statistics and data analysis. Established in 1992, this journal contains cutting-edge research, data, surveys, and more on numerical graphical displays and methods, and perception. Articles are written for readers who have a strong background in statistics but are not necessarily experts in computing. Published in March, June, September, and December.