贝叶斯自适应估算的有效参数空间压缩

IF 0.8 4区数学 Q3 STATISTICS & PROBABILITY

Communications in Statistics-Simulation and Computation Pub Date : 2024-07-11 DOI:10.1080/03610918.2024.2376867

Mingyao Li, Juanping Zhu

引用次数: 0

摘要

贝叶斯自适应估计在心理物理学的参数估计中发挥着重要作用。目前的研究重点是快速降低参数的不确定性，但参数估计需要大量的时间。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Effective parameter space compression for Bayesian adaptive estimation

Bayesian adaptive estimation plays an important role in the parameter estimation in Psychophysics. Current study focuses on the quick reduction of the uncertainty of the parameters, but the paramet...

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来源期刊

Communications in Statistics-Simulation and Computation 数学-统计学与概率论

CiteScore

2.50

自引率

11.10%

发文量

240

审稿时长

6 months

期刊介绍： The Simulation and Computation series intends to publish papers that make theoretical and methodological advances relating to computational aspects of Probability and Statistics. Simulational assessment and comparison of the performance of statistical and probabilistic methods will also be considered for publication. Papers stressing graphical methods, resampling and other computationally intensive methods will be particularly relevant. In addition, special issues dedicated to a specific topic of current interest will also be published in this series periodically, providing an exhaustive and up-to-date review of that topic to the readership.