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Updated: Jun 14, 2025

Basics of Multivariate Analysis in Neuroimaging Data
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Basics of Multivariate Analysis in Neuroimaging Data

Published on: July 24, 2010

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使用Wishart过程和顺序的蒙特卡洛过程,对动态共变率进行了强大的推断

Hester Huijsdens1, David Leeftink1, Linda Geerligs1

  • 1Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, Thomas van Aquinostraat 4, 6525 GD Nijmegen, The Netherlands.

Entropy (Basel, Switzerland)
|August 29, 2024
PubMed
概括

我们为Wishart过程开发了一种序列蒙特卡洛 (SMC) 采样器,改进了动态协差估计. 这种贝叶斯非参数方法提供了可靠的预测,超过了MCMC和变量推理,特别是在复杂的协差函数中.

关键词:
贝叶斯的推理 贝叶斯的推理马尔科夫链 蒙特卡洛 马尔科夫链连续的蒙特卡洛系列在Wishart的过程中,Wishart的流程.动态共变的动态共变性变化推理推理是变化的推理.

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