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Two Studies on the Application of Machine Learning for Biomedical Big Data
Survival Analysis Using Bayesian Joint Models
Marked Determinantal Point Processes
Bayesian Tractography Using Geometric Shape Priors
Envelopes, Subspace Learning and Applications
Bayesian Semiparametric Joint Model for Longitudinal and Survival Data
High-Dimensional Statistical Methods for Tensor Data and Efficient Algorithms
Univariate and Multivariate Volatility Models for Portfolio Value at Risk
Online Feature Selection with Annealing and Its Applications
Shape Based Function Estimation
Applications of Machine Learning to Precision Medicine
Bayesian Hierarchical Models That Incorporate New Sources of Dependence for Boundary Detection and Spatial Prediction
Leveraging Structural Information in Regression Tree Ensembles
Statistical Modeling and Testing of Shapes of Planar Objects
Examination of the Relationship between Alcohol and Dementia in a Longitudinal Study
Study of Some Issues of Goodness-of-Fit Tests for Logistic Regression
Elastic Functional Principal Component Analysis for Modeling and Testing of Functional Data
Elastic Functional Regression Model
Building a Model Performance Measure for Examining Clinical Relevance Using Net Benefit Curves
Non-Parametric and Semi-Parametric Estimation and Inference with Applications to Finance and Bioinformatics
Bayesian Analysis of Survival Data with Missing Censoring Indicators and Simulation of Interval Censored Data
Generalized Mahalanobis Depth in Point Process and Its Application in Neural Coding and Semi-Supervised Learning in Bioinformatics
Volatility Matrix Estimation for High-Frequency Financial Data
Wavelet-Based Bayesian Approaches to Sequential Profile Monitoring
Tests and Classifications in Adaptive Designs with Applications
Statistical Shape Analysis of Neuronal Tree Structures
Fused Lasso and Tensor Covariance Learning with Robust Estimation
Semiparametric Bayesian Regression Models for Skewed Responses
Comparative mRNA Expression Analysis Leveraging Known Biochemical Interactions
On the Statistical Modeling of Count Data in High Dimensions
Shape Constrained Single Index Models for Biomedical Studies
Influence Measures for Bayesian Data Analysis
Scalable Nonconvex Optimization Algorithms
Matched-Sample-Based Normalization Method
Examining the Effect of Treatment on the Distribution of Blood Pressure in the Population Using Observational Data
Semi-Parametric Generalized Estimating Equations with Kernel Smoother
Bayesian Modeling and Variable Selection for Complex Data
Spatial Statistics and Its Applications in Biostatistics and Environmental Statistics
Testing for the Equality of Two Distributions on High Dimensional Object Spaces and Nonparametric Inference for Location Parameters
Bayesian Wavelet Based Analysis of Longitudinally Observed Skewed Heteroscedastic Responses
Regression Methods for Skewed and Heteroscedastic Response with High-Dimensional Covariates
Nonparametric Change Point Detection Methods for Profile Variability
Scalable and Structured High Dimensional Covariance Matrix Estimation
Nonparametric Detection of Arbitrary Changes to Distributions and Methods of Regularization of Piecewise Constant Functional Data
High Level Image Analysis on Manifolds via Projective Shapes and 3D Reflection Shapes
Small Area Estimation with Random Effects Selection
Bayesian Models for Capturing Heterogeneity in Discrete Data
Robust Function Registration Using Depth on the Phase Variability
Intensity Estimation in Poisson Processes with Phase Variability
Sparse Feature and Element Selection in High-Dimensional Vector Autoregressive Models

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