Intrinsic regression models for positive-definite matrices with applications to diffusion tensor imaging

Keyphrases

• Regression Model 100%
• Diffusion Tensor Imaging 100%
• Positive Definite Matrix 100%
• Statistical Significance 40%
• Euclidean Space 40%
• Riemannian Manifold 40%
• Linear Hypothesis 40%
• AIDS/HIV 20%
• White Matter 20%
• Parameter Estimation 20%
• Region of Interest 20%
• Large Region 20%
• Resampling Methods 20%
• Medical Imaging 20%
• Simulation Study 20%
• Motivation 20%
• Model Use 20%
• Multivariate Regression 20%
• Proposed Methodology 20%
• Diffusion Tensor 20%
• Finite Sample Performance 20%
• Familywise Error Rate 20%
• Link Function 20%
• Limiting Distribution 20%
• Real Application 20%
• Vector Space 20%
• Semiparametric Model 20%
• Score Statistic 20%
• Diagnostic Effect 20%
• Estimation Procedures 20%
• Supplemental Materials 20%

Mathematics

• Regression Model 100%
• Tensor 100%
• Positive Definite Matrix 100%
• Intrinsic Property 100%
• Covariate 60%
• Statistical Significance 40%
• Test Procedure 40%
• Euclidean Space 40%
• Riemannian Manifolds 40%
• Simulation Study 20%
• Resampling Method 20%
• Multivariate Regression 20%
• Limiting Distribution 20%
• Parameter Estimate 20%
• Score Statistic 20%
• Wise Error Rate 20%
• Vector Space 20%