MARC details
| 000 -LEADER |
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| fixed length control field |
02441cam a2200301 a 4500 |
| 003 - CONTROL NUMBER IDENTIFIER |
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| control field |
EG-GiCUC |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
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| fixed length control field |
161225s2016 ua d f m 000 0 eng d |
| 040 ## - CATALOGING SOURCE |
|---|
| Original cataloging agency |
EG-GiCUC |
| Language of cataloging |
eng |
| Transcribing agency |
EG-GiCUC |
| 041 0# - LANGUAGE CODE |
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| Language code of text/sound track or separate title |
eng |
| 049 ## - LOCAL HOLDINGS (OCLC) |
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| Holding library |
Deposite |
| 097 ## - Thesis Degree |
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| Thesis Level |
M.Sc |
| 099 ## - LOCAL FREE-TEXT CALL NUMBER (OCLC) |
|---|
| Classification number |
Cai01.03.01.M.Sc.2016.Wa.H |
| 100 0# - MAIN ENTRY--PERSONAL NAME |
|---|
| Personal name |
Wafaa Ibrahim Mohamed Ibrahim |
| 245 10 - TITLE STATEMENT |
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| Title |
Heavy-tailed longitudinal data : |
| Remainder of title |
An adaptive linear regression approach / |
| Statement of responsibility, etc. |
Wafaa Ibrahim Mohamed Ibrahim ; Supervised Ahmed Mahmoud Gad |
| 246 15 - VARYING FORM OF TITLE |
|---|
| Title proper/short title |
البيانات الطولية كثيفة الاطراف : |
| Remainder of title |
اسلوب انحدار خطي تكيفي |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. |
|---|
| Place of publication, distribution, etc. |
Cairo : |
| Name of publisher, distributor, etc. |
Wafaa Ibrahim Mohamed Ibrahim , |
| Date of publication, distribution, etc. |
2016 |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
83 P. : |
| Other physical details |
charts ; |
| Dimensions |
25cm |
| 502 ## - DISSERTATION NOTE |
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| Dissertation note |
Thesis (M.Sc.) - Cairo University - Faculty of Economics and Political Science - Department of Statistics |
| 520 ## - SUMMARY, ETC. |
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| Summary, etc. |
Longitudinal studies play a prominent role in many social and economics fields. They are indispensable to the study of change in an outcome over time. Special statistical analysis techniques are needed for longitudinal data to accommodate the potential patterns of correlation and variation that might be combined to produce a complicated covariance structure Most of the estimation methods for longitudinal models are based on multivariate normal distribution assumption. However, in many situations this assumption may be violated, for example if the error distribution is heavy tailed. Hence, a proper estimation method is needed in such situations. The least absolute deviation (LAD) estimator minimizes the absolute deviation errors. The adaptive linear regression estimate (ALR) is a linear combination of ordinary least squares (OLS) and least absolute deviations (LAD) are used in case of heavy-tailed cross-sectional data. In the present thesis the least absolute deviation (LAD) estimator developed to accommodate heavy tailed longitudinal data. Also, the adaptive linear regression estimator (ALR) is coined and applied to heavy tailed longitudinal data. Simulation studies are conducted to evaluate the proposed techniques, in addition to applying modified estimators on a real data set |
| 530 ## - ADDITIONAL PHYSICAL FORM AVAILABLE NOTE |
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| Additional physical form available note |
Issued also as CD |
| 653 #4 - INDEX TERM--UNCONTROLLED |
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| Uncontrolled term |
Heavy-tailed longitudinal data |
| 653 #4 - INDEX TERM--UNCONTROLLED |
|---|
| Uncontrolled term |
Least Absolute Deviations (LAD |
| 653 #4 - INDEX TERM--UNCONTROLLED |
|---|
| Uncontrolled term |
Robust estimator |
| 700 0# - ADDED ENTRY--PERSONAL NAME |
|---|
| Personal name |
Ahmed Mahmoud Gad , |
| Relator term |
|
| 905 ## - LOCAL DATA ELEMENT E, LDE (RLIN) |
|---|
| Cataloger |
Enas |
| Reviser |
Cataloger |
| 905 ## - LOCAL DATA ELEMENT E, LDE (RLIN) |
|---|
| Cataloger |
Nazla |
| Reviser |
Revisor |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
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| Source of classification or shelving scheme |
Dewey Decimal Classification |
| Koha item type |
Thesis |
