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| JDZ7210 | Parameter Est. For Linear Models in Geodesy | 3+0+0 | ECTS:7.5 | | Year / Semester | Spring Semester | | Level of Course | Third Cycle | | Status | Elective | | Department | DEPARTMENT of GEOMATICS ENGINEERING | | Prerequisites and co-requisites | None | | Mode of Delivery | Face to face, Practical | | Contact Hours | 14 weeks - 3 hours of lectures per week | | Lecturer | Prof. Dr. Mualla YALÇINKAYA | | Co-Lecturer | None | | Language of instruction | Turkish | | Professional practise ( internship ) | None | | | | The aim of the course: | | Examine parameter estimation methods for linear models in geodetic problems. |
| Programme Outcomes | CTPO | TOA | | Upon successful completion of the course, the students will be able to : | | | | PO - 1 : | learn parameter estimation methods | 1,2,5 | 1,3 | | PO - 2 : | examine Gauss-Markoff Model and its applications in Geodesy in detail | 1,2,3,5 | 1,3 | | PO - 3 : | study on linearization of geodetic problems and Least-squares method | 1,2 | 1,3 | | PO - 4 : | research on special Gauss-Markoff Models and applications in Geodesy. | 1,2,3,5 | 1,3,5 | | CTPO : Contribution to programme outcomes, TOA :Type of assessment (1: written exam, 2: Oral exam, 3: Homework assignment, 4: Laboratory exercise/exam, 5: Seminar / presentation, 6: Term paper), PO : Learning Outcome | | |
| Methods of Estimating Parameter, Gauss-Markoff Model and applications in Geodesy, Definition of linearization, Method of Least Squares, Maximum-Likelihood method, Recursive parameter estimation, Special Gauss-Markoff Models (polynomial model, analysis of variance) , Regression model, Estimation of variance and covariance components, Robust parameter estimation. |
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| Course Syllabus | | Week | Subject | Related Notes / Files | | Week 1 | Introduction for Estimating Parameter on geodetic linear models. | | | Week 2 | Methods of Estimating Parameter, | | | Week 3 | Gauss-Markoff Model and applications in Geodesy. | | | Week 4 | Definition of linearization. | | | Week 5 | Method of Least Squares. | | | Week 6 | Maximum-Likelihood method. | | | Week 7 | Recursive parameter estimation. | | | Week 8 | Mid-term exam | | | Week 9 | Special Gauss-Markoff Models (polynomial model, analysis of variance). | | | Week 10 | Regression model. | | | Week 11 | Estimation of variance and covariance components. | | | Week 12 | Robust parameter estimation. | | | Week 13 | Repeat | | | Week 14 | Presentation of exercises. | | | Week 15 | Duties presentation. | | | Week 16 | End-of-term exam | | | |
| 1 | Koch, K.R. 1999; Parameter Estimation and Hypothesis Testing in Linear Models, Springer-Verlag, Berlin, Germany. | | | |
| 1 | Sjöberg, L.E. 1985; Adjustment and variance-covariance component estimation with a singular covariance matrix. Z Vermessunswesen, 110: 145-151. | | | 2 | Kampmann, G. 1994; Robuste Deformationsanalyse mittels balancierter Ausgleichung. Allgemeine Vermessungs Nachrichten, 101: 8-17. | | | |
| Method of Assessment | | Type of assessment | Week No | Date | Duration (hours) | Weight (%) | | Mid-term exam | 9 | | 2 | 30 | | Presentation | 14 | | 1 | 10 | | Homework/Assignment/Term-paper | 5
6
7
8
9
10
11
12 | | 18 | 10 | | End-of-term exam | 15 | | 2 | 50 | | |
| Student Work Load and its Distribution | | Type of work | Duration (hours pw) | No of weeks / Number of activity | Hours in total per term | | Yüz yüze eğitim | 3 | 14 | 42 | | Sınıf dışı çalışma | 3 | 10 | 30 | | Arasınav için hazırlık | 10 | 1 | 10 | | Arasınav | 2 | 1 | 2 | | Ödev | 8 | 8 | 64 | | Dönem sonu sınavı için hazırlık | 8 | 1 | 8 | | Dönem sonu sınavı | 2 | 1 | 2 | | Diğer 1 | 10 | 3 | 30 | | Total work load | | | 188 |
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