Statistical Learning

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Neuroimaging data analysis (NDA) has recently emerged as part of the rapidly evolving field of big and complex data analysis. Neuroimaging data, for example, diffusion tensor imaging (DTI) and magnetic resonance imaging (MRI), could be treated as functional data while having its own features. Therefore, its statistical analysis inherits some methods from functional data analysis (FDA) and also poses new challenges due to its complex structure. To address those challenges, we develop novel statistical methods in FDA and NDA to explore its complex and correlated structures and integrate data from other resources such as clinical data and genetics data.