GMPE240 Parameter Estimation
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Showing course contents for the educational year 2022 - 2023 .
Course responsible: Ola Øvstedal
Teachers: Jon Glenn Omholt Gjevestad
ECTS credits: 10
Faculty: Faculty of Science and Technology
Teaching language: NO
Teaching exam periods:
This course starts in Spring parallel. This course has teaching/evaluation in Spring parallel, .
Course frequency: Annually
First time: Study year 2018-2019
Optimal estimation of parameters (e.g. coordinates). Methods to detect outliers in observations. Quantification of integrity in the form of computed numbers for reliability. Introduction to sequential methods and Kalman filtering.
Master parameter estimation and propagation of errors. Have knowledge of and ability to carry out outlier detection and reliability analyses, sequential adjustment and Kalman filtering. Have knowledge of robust estimation, conditional adjustment and parameter adjustment with conditions.
Lectures and exercises.
Teaching support will be given primarily in connection with that part of the structured teaching that is set aside for exercise guidance. It will also be possible to communicate directly with the course teacher by appointment during office hours.
Ghilani, C.D., Adjustment computations - Spatial data analysis, Sixth edition, Wiley,
Supplementary literature in the form of lecture notes and articles (made available on the course website).
MATH113 or MATH131, STAT100
Final written examination of 3.5 hours.
Special requirements in Science
Type of course:
Lectures: 52 hours. Exercises: 52 hours.
The external and internal examiner jointly prepare the exam questions and the correction manual. The external examiner reviews the internal examiner's examination results by correcting a random sample of candidate¿s exams as a calibration according to the Department's guidelines for examination markings.
Allowed examination aids: C3 All types of calculators, all other aids – including digital aids
Examination details: One written exam: Letter grades