Application of Spatial Bayesian Hierarchical Model with Variable Selection to fMRI data
碩士 === 國立成功大學 === 統計學系 === 103 === We propose a spatial Bayesian hierarchical model to analyze functional magnetic resonance imaging data with complex spatial and temporal structures. Several studies have found that the spatial dependence not only appear in signal changes but also in temporal correl...
Main Authors: | Xin-HanHuang, 黃信翰 |
---|---|
Other Authors: | Kuo-Jung Lee |
Format: | Others |
Language: | en_US |
Published: |
2015
|
Online Access: | http://ndltd.ncl.edu.tw/handle/18746413115126691555 |
Similar Items
-
An Application of Bayesian Hierarchical Linear Modeling to an Event-Related fMRI Study
by: Fu-JunHuang, et al.
Published: (2014) -
BayesFactorFMRI: Implementing Bayesian Second-Level fMRI Analysis with Multiple Comparison Correction and Bayesian Meta-Analysis of fMRI Images with Multiprocessing
by: Hyemin Han
Published: (2021-02-01) -
Multivariate spatial feature selection in fMRI
by: Chang, L.J, et al.
Published: (2021) -
Bayesian Inference for Functional Dynamics Exploring in fMRI Data
by: Xuan Guo, et al.
Published: (2016-01-01) -
Search for patterns of functional specificity in the brain: A nonparametric hierarchical Bayesian model for group fMRI data
by: Lashkari, Danial, et al.
Published: (2016)