High‐dimensional data common in genomics, proteomics, and chemometrics often contains
complicated correlation structures. Recently, partial least squares (PLS) and Sparse PLS …

Data analysis on non-Euclidean spaces, such as tree spaces, can be challenging. The main
contribution of this article is establishment of a connection between tree-data spaces and the …

This article discusses a study of cell images in cell culture biology from an object-oriented
point of view. The motivation of this research is to develop a statistical approach to cell …

Object Oriented Data Analysis of Cell Images and Analysis of Elastic Functions Page 1
Object Oriented Data Analysis of Cell Images and Analysis of Elastic Functions Xiaosun Lu …

LATENT SUPERVISED LEARNING AND DIPROPERM Susan Wei A dissertation submitted to
the faculty at the University of North Carolina a Page 1 LATENT SUPERVISED LEARNING …

In the first part of the dissertation, we propose a multiscale model for Gaussian noised
images under a Bayesian framework for both 2-dimensional (2D) and 3-dimensional (3D) …

Object oriented data analysis (OODA) aims at statistically analyzing populations of
complicated objects. This paper is motivated by a study of cell images in cell culture biology …