Publication:
Robust Wavelet Regression With Automatic Boundary Correction

Thumbnail Image
Date
2012-12
Authors
Alsaidi Almahdi Mohamed Altaher
Journal Title
Journal ISSN
Volume Title
Publisher
Research Projects
Organizational Units
Journal Issue
Abstract
This thesis proposes different robust methods in an attempt to keep using the idea of PWR and LP\iVR even beyond the usual assumptions of such outliers, independent or correlated non Gaussian noises and random missing data. Therefore, this thesis is divided into three parts. The first part introduces five different robust methodologies to extend the validity of PWR and LPWR to describe data contaminated with outliers and independent noises. The second part pays special exception when the noise structure is correlated.
Description
Keywords
Robust Wavelet Regression , Automatic Boundary Correction
Citation
URI
https://erepo.usm.my/handle/123456789/19516
Collections
Pusat Pengajian Sains Matematik - Tesis