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Some applications of Erdos-Baum-Katz type theorems in high-dimensional data
| Content Provider | Semantic Scholar |
|---|---|
| Author | Wang, Yueleng |
| Copyright Year | 2017 |
| Abstract | In this thesis, we consider an estimation problem concerning the matrix of correlation coefficients 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 Erdös-BaumKatz 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. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | https://scholar.uwindsor.ca/cgi/viewcontent.cgi?article=7025&context=etd&httpsredir=1&referer= |
| Alternate Webpage(s) | http://scholar.uwindsor.ca/cgi/viewcontent.cgi?article=7025&context=etd |
| Alternate Webpage(s) | https://scholar.uwindsor.ca/cgi/viewcontent.cgi?article=7025&context=etd |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
