Date of Award

2017

Publication Type

Master Thesis

Degree Name

M.Sc.

Department

Mathematics and Statistics

First Advisor

Nkurunziza, Severien

Rights

info:eu-repo/semantics/openAccess

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 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.

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