Date of Award
2017
Publication Type
Master Thesis
Degree Name
M.Sc.
Department
Mathematics and Statistics
Supervisor
Nkurunziza, Severien
Rights
info:eu-repo/semantics/openAccess
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Abstract
In this thesis, we consider an estimation problem concerning the matrix of correlation coe cients in context of high dimensional data settings. In particular, we generalise four main theorems in Li and Rosalsky [Li, D. and Rosalsky, A. (2006). Some strong limit theorems for the largest entries of sample correlation matrices, The Annals of Applied Probability, 16, 1, 423{447]. In addition, by using Erdos-Baum- Katz type Theorems, we also simplify remarkably the proofs of some results of Li and Rosalsky (2006). Further, we generalize a theorem which is useful in deriving the existence of the pth moment as well as in studying the convergence rates in Law of Large Numbers.
Recommended Citation
Wang, Yueleng, "Some applications of Erdos-Baum-Katz type theorems in high-dimensional data" (2017). Electronic Theses and Dissertations. 6023.
https://scholar.uwindsor.ca/etd/6023