Please use this identifier to cite or link to this item:
Title: Approximating the distributions of x2-type mixtures via matching four cumulants
Authors: LIANG YU
Keywords: x2-type mixtures;Local Polynomial Smoothing;Nonparametric Goodness-of-fit Test
Issue Date: 1-Dec-2004
Citation: LIANG YU (2004-12-01). Approximating the distributions of x2-type mixtures via matching four cumulants. ScholarBank@NUS Repository.
Abstract: Nonparametric goodness-of-fit tests often result in test statistic which can be written as a random variable of chi-square-type mixtures. Zhang (2003) proposed to approximate its distribution using a random variable of form chi-square-type mixtures via matching the first three cumulants. In this thesis, we attempt to improve this approximation via matching the first four cumulants using a random variable of form non-central chi-square mixtures, resulting in the so-called non-central chi-square-approximation. Application of the results to nonparametric goodness-of-fit test based on local polynomial smoother is investigated. Two simulation studies are conducted to compare the non-central chi-square-approximation, the central chi-square-approximation and the normal approximation numerically. The methodologies are illustrated using a real data example.
Appears in Collections:Master's Theses (Open)

Show full item record
Files in This Item:
File Description SizeFormatAccess SettingsVersion 
HT026316U_thesis.pdf505.15 kBAdobe PDF



Page view(s)

checked on Dec 16, 2018


checked on Dec 16, 2018

Google ScholarTM


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