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Principal Investigator  
Principal Investigator's Name: Guanqun Cao
Institution: Auburn University
Department: Math & Stats
Proposed Analysis: Motivated by the analysis of imaging data, we propose a novel functional data analysis model to carry out the regression analysis of functional response data. We apply the proposed mathod to investigate the development of white matter diffusivities along the corpus callosum skeleton obtained from Alzheimer’s Disease Neuroimaging Initiative (ADNI) study
Additional Investigators  
Investigator's Name: Zuofeng Shang
Proposed Analysis: In this work, we propose a deep neural networks based method to perform nonparametric regression for functional data. The proposed estimators are based on sparsely connected deep neural networks with ReLU activation function. We provide the convergence rate of the proposed deep neural networks estimator in terms of the empirical norm. Through Monte Carlo simulation studies we examine the finite-sample performance of the proposed method. Finally, the proposed method is applied to analyze positron emission tomography images of patients with Alzheimer disease obtained from the Alzheimer Disease Neuroimaging Initiative database.