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Information
| Unit | INSTITUTE OF NATURAL AND APPLIED SCIENCES |
| STATISTICS (PhD) | |
| Code | ISB568 |
| Name | Robust Regression |
| Term | 2018-2019 Academic Year |
| Term | Spring |
| Duration (T+A) | 3-0 (T-A) (17 Week) |
| ECTS | 6 ECTS |
| National Credit | 3 National Credit |
| Teaching Language | Türkçe |
| Level | Belirsiz |
| Type | Normal |
| Mode of study | Yüz Yüze Öğretim |
| Catalog Information Coordinator | Prof. Dr. ALİ İHSAN GENÇ |
| Course Instructor |
The current term course schedule has not been prepared yet.
|
Course Goal / Objective
The aim of this course is to teach students robust statistical methods in regression and how to use them.
Course Content
Regression M-estimation, breakdown point, robust tests, multiple regression and M-estimation, computation of M-estimators, L-estimation, S-estimation, LTS-estimation, robust confidence intervals, elliptical distributions, generalized linear models.
Course Precondition
Resources
Notes
Course Learning Outcomes
| Order | Course Learning Outcomes |
|---|---|
| LO01 | Finds M-estimators in regression. |
| LO02 | Computes M-estimators in regression. |
| LO03 | Comprehends robust statistical methods. |
| LO04 | Computes robust confidence intervals. |
| LO05 | Performs robust hypothesis tests. |
Relation with Program Learning Outcome
| Order | Type | Program Learning Outcomes | Level |
|---|
Week Plan
| Week | Topic | Preparation | Methods |
|---|---|---|---|
| 1 | Classical regression and regression M estimation | Source reading | |
| 2 | Regression M-estimation | Source reading | |
| 3 | Breakdown point | Source reading | |
| 4 | Robust tests for linear hypotheses | Source reading | |
| 5 | Multiple regression and M estimation | Source reading | |
| 6 | Multiple regression and M estimation | Source reading | |
| 7 | Computation of M estimates | Source reading | |
| 8 | Mid-Term Exam | Reviewing | |
| 9 | Computation of M estimates | Source reading | |
| 10 | L-estimates, S-estimates, LTS estimates | Source reading | |
| 11 | Robust confidence intervals | Source reading | |
| 12 | Robust principal components | Source reading | |
| 13 | Elliptical distributions | Source reading | |
| 14 | Generalized linear models | Source reading | |
| 15 | Generalized linear models | Source reading | |
| 16 | Term Exams | Reviewing | |
| 17 | Term Exams | Reviewing |