Comparison of methods for detecting outliers with distributions for estimating time series models / (Record no. 171678)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 05240namaa22004211i 4500 |
| 003 - CONTROL NUMBER IDENTIFIER | |
| control field | OSt |
| 005 - أخر تعامل مع التسجيلة | |
| control field | 20250519103936.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 250423s2024 ua a|||frm||| 000 0 eng d |
| 040 ## - CATALOGING SOURCE | |
| Original cataloguing agency | EG-GICUC |
| Language of cataloging | eng |
| Transcribing agency | EG-GICUC |
| Modifying agency | EG-GICUC |
| Description conventions | rda |
| 041 0# - LANGUAGE CODE | |
| Language code of text/sound track or separate title | eng |
| Language code of summary or abstract | eng |
| -- | ara |
| 049 ## - Acquisition Source | |
| Acquisition Source | Deposit |
| 082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER | |
| Classification number | 519.5 |
| 092 ## - LOCALLY ASSIGNED DEWEY CALL NUMBER (OCLC) | |
| Classification number | 519.5 |
| Edition number | 21 |
| 097 ## - Degree | |
| Degree | M.Sc |
| 099 ## - LOCAL FREE-TEXT CALL NUMBER (OCLC) | |
| Local Call Number | Cai01.18.04.M.Sc.2024.Mo.C |
| 100 0# - MAIN ENTRY--PERSONAL NAME | |
| Authority record control number or standard number | Mohamed Ezzat Abdelaziz, |
| Preparation | preparation. |
| 245 10 - TITLE STATEMENT | |
| Title | Comparison of methods for detecting outliers with distributions for estimating time series models / |
| Statement of responsibility, etc. | by Mohamed Ezzat Abdelaziz ; Supervised Prof. Ahmad Amin Elsheikh, Dr. Amal Mohamed Abd-Elfatah. |
| 246 15 - VARYING FORM OF TITLE | |
| Title proper/short title | مقارنة طرق الكشف عن القيم المتطرفة مع التوزيعات لتقدير نماذج السلاسل الزمنية / |
| 264 #0 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE | |
| Date of production, publication, distribution, manufacture, or copyright notice | 2024. |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | 273 leaves : |
| Other physical details | illustrations ; |
| Dimensions | 25 cm. + |
| Accompanying material | CD. |
| 336 ## - CONTENT TYPE | |
| Content type term | text |
| Source | rda content |
| 337 ## - MEDIA TYPE | |
| Media type term | Unmediated |
| Source | rdamedia |
| 338 ## - CARRIER TYPE | |
| Carrier type term | volume |
| Source | rdacarrier |
| 502 ## - DISSERTATION NOTE | |
| Dissertation note | Thesis (M.Sc)-Cairo University, 2024. |
| 504 ## - BIBLIOGRAPHY, ETC. NOTE | |
| Bibliography, etc. note | Bibliography: pages 130-135. |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc. | An outlier is a data value that is unusually small or large or deviates from the pattern of the rest of the data. The subject of outliers has attracted a great deal of attention in the last decades, so the study of outliers is not a new phenomenon. Most real-world data sets contain outliers that have unusually large or small values when compared with others in the data set and it may cause a negative effect on data analysis. There are different methods and tests for detecting outliers according to the type of data which are:<br/>• Methods and tests for cross-section data that follow a specific distribution.<br/>• Methods and tests for time series data.<br/> This study is concerned with detecting the outliers in time series data that follows a specific distribution, so two models were considered which are the Exponential Autoregressive model of order one EAR(1) and the Gamma Autoregressive model of order one GAR(1), and two types of outliers additive outlier (AO) and innovational outlier (IO) were generated in each model, then three methods/tests which are ARIMA-AO(IO), Modified Z-score and Rosner were applied in each model to detect the outliers. An EAR(1) model is an Autoregressive model whose data follows Exponential distribution and a GAR(1) model is an Autoregressive model whose data follows Gamma distribution. For comparison between the best performance, methods and tests of cross-section data (Modified Z-score & Rosner) and time series data (ARIMA-AO(IO)) were applied. Three criteria of performance were used to measure the performance of each method which are Recall, Precision and F-measure. |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc. | تحتوي معظم البيانات الحقيقية على مشاهدات قد تكون كبيرة او صغيرة بشكل غير عادى عند مقارانتها بالقيم الأخرى فى مجموعة البيانات. وقد يكون لهذه المشاهدات الشاذة المعروفة بأنها (قيم شاذة) تأثير سلبي على تحليل البيانات مثل تقديرات الانحدار والتنبؤ وتحليل التباين و غيرذلك<br/>والقيم المتطرفة هي أدوات قوية لتحديد الاحداث الاكثر إثارة للاهتمام في بيانات المجتمع ويمكن<br/>انتقاء الاحداث المهمة تاريخيًا من خلال الكشف عن القيم الشاذة في مجموعات بيانات السلاسل الزمنية.<br/> تم عرض العديد من تقنيات الكشف عن القيم المتطرفة في هذه الدراسة. هناك نوعان من طرق الكشف عن القيم المتطرفة بالنسبة لنوع البيانات هما<br/>.1 طرق كشف تستخدم مع التوزيعات االحصائية (البيانات المقطعية التى تتبع توزيع معين)<br/>.2 طرق كشف تستخدم مع بيانات السالسل الزمنية<br/>وهذة الدراسة تهتم بالكشف عن القيم الشاذة فى بيانات السالسل الزمنية التى تتبع توزيع معين و تمت الدراسة على نموذجين<br/>هما<br/>Exponential autoregressive EAR 1 نموذج الانحدار الذاتي الاسي من الرتبة الاولي 1<br/>Gamma Autoregressive GAR 1 نموذج الانحدار الذاتي لجاما من الرتبة الاولي 2<br/> |
| 530 ## - ADDITIONAL PHYSICAL FORM AVAILABLE NOTE | |
| Issues CD | Issues also as CD. |
| 546 ## - LANGUAGE NOTE | |
| Text Language | Text in English and abstract in Arabic & English. |
| 650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | Mathematical statistics |
| Source of heading or term | qrmak |
| 653 #0 - INDEX TERM--UNCONTROLLED | |
| Uncontrolled term | Outlier |
| -- | Time series |
| -- | ARIMA |
| -- | Autoregressive |
| -- | Detection |
| -- | Exponential |
| -- | Gamma |
| -- | Extreme value |
| -- | Additive outlier |
| -- | Innovational outlier |
| -- | Simulation |
| -- | Robust |
| 700 0# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Ahmad Amin Elsheikh |
| Relator term | thesis advisor. |
| 700 0# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Amal Mohamed Abd-Elfatah |
| Relator term | thesis advisor. |
| 900 ## - Thesis Information | |
| Grant date | 01-01-2024 |
| Supervisory body | Ahmad Amin Elsheikh |
| -- | Amal Mohamed Abd-Elfatah |
| Universities | Cairo University |
| Faculties | Faculty of Graduate Studies for Statistical Research |
| Department | Department of Applied Statistics and Econometrics |
| 905 ## - Cataloger and Reviser Names | |
| Cataloger Name | Shimaa |
| Reviser Names | Eman Ghareb |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Source of classification or shelving scheme | Dewey Decimal Classification |
| Koha item type | Thesis |
| Edition | 21 |
| Suppress in OPAC | No |
| Source of classification or shelving scheme | Home library | Current library | Date acquired | Inventory number | Full call number | Barcode | Date last seen | Effective from | Koha item type |
|---|---|---|---|---|---|---|---|---|---|
| Dewey Decimal Classification | المكتبة المركزبة الجديدة - جامعة القاهرة | قاعة الرسائل الجامعية - الدور الاول | 23.04.2025 | 91035 | Cai01.18.04.M.Sc.2024.Mo.C | 01010110091035000 | 23.04.2025 | 23.04.2025 | Thesis |