PřF:M9901 Spline smoothing - Course Information
M9901 Theory and practice of spline smoothingFaculty of Science
- Extent and Intensity
- 2/2/0. 4 credit(s) (fasci plus compl plus > 4). Type of Completion: zk (examination).
- doc. PaedDr. RNDr. Stanislav Katina, Ph.D. (lecturer)
Mgr. Zdeňka Geršlová (seminar tutor)
Mgr. Vojtěch Šindlář (seminar tutor)
- Guaranteed by
- doc. PaedDr. RNDr. Stanislav Katina, Ph.D.
Department of Mathematics and Statistics - Departments - Faculty of Science
Contact Person: doc. PaedDr. RNDr. Stanislav Katina, Ph.D.
Supplier department: Department of Mathematics and Statistics - Departments - Faculty of Science
- Mon 17. 9. to Fri 14. 12. Wed 8:00–9:50 M3,01023
- Timetable of Seminar Groups:
- Course Enrolment Limitations
- The course is also offered to the students of the fields other than those the course is directly associated with.
- fields of study / plans the course is directly associated with
- Course objectives
- The main goal of the course is to become familiar with interpolation and smoothing using one- and multivariate splines, outlier detection with applications to electrocardiology, electroencephalography, shape analysis (geometrical morphometrics) on biological objects, statistical analyses of multivariate data, testing of multivariate statistical hypotheses, multivariate SVD models (e.g. generalized PCA), 2D/3D statistical visualisation and implementation to R language.
- Learning outcomes
- Student will be able:
- to understand principles of spline interpolation and smoothing for curves and surfaces;
- to build up and explain suitable model for curves and surfaces;
- to apply spline interpolation and smoothing to real data;
- to implement methods of spline interpolation and smoothing to R.
- geometric transformations in 2D and 3D,
- multivariate splines, functional models,
- identification of anatomical landmarks, curves, and surfaces,
- testing of multivariate statistical hypotheses,
- multivariate statistical methods for EEG, ECG, and morphometric data,
- 2D/3D statistical graphics
- recommended literature
- JOHNSON, Richard A. and Dean W. WICHERN. Applied multivariate statistical analysis. 3rd ed. Englewood Cliffs: Prentice-Hall, 1992. xiv, 642 s. ISBN 0-13-041807-2. info
- not specified
- CASELLA, George and Roger L. BERGER. Statistical inference. 2nd ed. Pacific Grove, Calif.: Duxbury, 2002. xxviii, 66. ISBN 0534243126. info
- Teaching methods
- lectures, practicals, homework
- Assessment methods
- homework, oral exam
- Language of instruction
- Further Comments
- Study Materials
The course is taught annually.