Robust Wavelet Regression With Automatic Boundary Correction
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 introduce...
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my-usm-ep.607602024-06-26T03:10:03Z Robust Wavelet Regression With Automatic Boundary Correction 2012-12 Mohamed Altaher, Alsaidi Almahdi QA1-939 Mathematics 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. 2012-12 Thesis http://eprints.usm.my/60760/ http://eprints.usm.my/60760/1/Pages%20from%20Alsaidi.pdf application/pdf en public phd doctoral Universiti Sains Malaysia Pusat Pengajian Sains Matematik ( School of Mathematical Sciences) |
| institution |
Universiti Sains Malaysia |
| collection |
USM Institutional Repository |
| language |
English |
| topic |
QA1-939 Mathematics |
| spellingShingle |
QA1-939 Mathematics Mohamed Altaher, Alsaidi Almahdi Robust Wavelet Regression With Automatic Boundary Correction |
| description |
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. |
| format |
Thesis |
| qualification_name |
Doctor of Philosophy (PhD.) |
| qualification_level |
Doctorate |
| author |
Mohamed Altaher, Alsaidi Almahdi |
| author_facet |
Mohamed Altaher, Alsaidi Almahdi |
| author_sort |
Mohamed Altaher, Alsaidi Almahdi |
| title |
Robust Wavelet Regression With Automatic Boundary Correction |
| title_short |
Robust Wavelet Regression With Automatic Boundary Correction |
| title_full |
Robust Wavelet Regression With Automatic Boundary Correction |
| title_fullStr |
Robust Wavelet Regression With Automatic Boundary Correction |
| title_full_unstemmed |
Robust Wavelet Regression With Automatic Boundary Correction |
| title_sort |
robust wavelet regression with automatic boundary correction |
| granting_institution |
Universiti Sains Malaysia |
| granting_department |
Pusat Pengajian Sains Matematik ( School of Mathematical Sciences) |
| publishDate |
2012 |
| url |
http://eprints.usm.my/60760/1/Pages%20from%20Alsaidi.pdf |
| _version_ |
1804888994937307136 |