Back to Departmental Colloquium: Spring 2017
Departmental Colloquium
Date: Thursday, Feb 2, 2017
Time: 4:00PM
Location: JWB 335
Dan Shen
University of South Florida
Title |
Dimension Reduction of Neuroimaging Data Analysis |
Abstract |
High dimensionality has become a common feature of “big data” encountered in many divergent fields, such as neuroimaging and genetic analysis, which provides modern challenges for statistical analysis. To cope with the high dimensionality, dimension reduction becomes necessary. Principal component analysis (PCA) is arguably the most popular classical dimension reduction technique, which uses a few principal components (PCs) to explain most of the data variation. We introduce Multiscale Weighted Principal Component Regression (MWPCR), a new variation of PCA, for neuroimaging analysis. MWPCR introduces two sets of novel weights, including global and local spatial weights, to enable a selective treatment of individual features and incorporation of class label information as well as spatial pattern within neuroimaging data. Simulation studies and real data analysis show that MWPCR outperforms several competing methods. |
Mathematical Biology
Computational Mathematics
Applied Mathematics