Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/15593
Title: Almost sure limit of the smallest eigenvalue of sample correlation matrix
Authors: XIAO HAN
Keywords: sample covariance matrix, sample correlation matrix, smallest eigenvalue, random matrix, spectral distribution, Marcenko-Pastur law
Issue Date: 29-Nov-2006
Source: XIAO HAN (2006-11-29). Almost sure limit of the smallest eigenvalue of sample correlation matrix. ScholarBank@NUS Repository.
Abstract: Suppose we have a data matrix consisting of independent and identically distributed entries with finite fourth moment, we show that the smallest eigenvalue of the sample correlation matrix converges almost surely to a constant provided that the ration of dimensions of the data matrix goes to a positive constant. We accomplish this by establishing a similar result for the sample covariance matrix. The proof relies strongly on existing results about the simplified sample covariance matrix.
URI: http://scholarbank.nus.edu.sg/handle/10635/15593
Appears in Collections:Master's Theses (Open)

Show full item record
Files in This Item:
File Description SizeFormatAccess SettingsVersion 
XIAOH.PDF322.88 kBAdobe PDF

OPEN

NoneView/Download

Page view(s)

231
checked on Dec 11, 2017

Download(s)

357
checked on Dec 11, 2017

Google ScholarTM

Check


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.