Bi8773 Practicals in shape analysis

Faculty of Science
Spring 2019
Extent and Intensity
0/2/0. 2 credit(s). Type of Completion: z (credit).
Teacher(s)
doc. PaedDr. RNDr. Stanislav Katina, Ph.D. (lecturer)
doc. RNDr. Miroslav Králík, Ph.D. (lecturer)
Mgr. Stanislav Zámečník (seminar tutor)
Mgr. Zdeňka Geršlová (assistant)
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
Timetable of Seminar Groups
Bi8773/01: Mon 18. 2. to Fri 17. 5. Mon 12:00–13:50 MP1,01014
Prerequisites
Basic knowledge of applied statistics and R programming, prerequisites MAS01 and MaS02.
Course Enrolment Limitations
The course is offered to students of any study field.
Course objectives
The aim of this course is to practice students in computational methods of geometric morphometrics that are usable in anthropological research.
Learning outcomes
At the end of this course the students should be able to:
understand and explain basic principles of traditional and geometric morphometrics (shape analysis), perform manual and (semi)automatic identification of anatomical landmarks, curves, and surfaces on the biological objects;
understand multivariate statistical methods for EEG, ECG, and morphometric data (multivariate SVD models, multivariate splines, multivariate regression, functional and Fourier models);
interpret 2D/3D statistical visualisation.
Syllabus
  • - geometric transformations in 2D and 3D;
  • - multivariate splines, functional and Fourier models;
  • - (semi)automatic 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
Literature
    recommended literature
  • Applied multivariate statistical analysis. Edited by Richard Arnold Johnson - Dean W. Wichern. 6th ed. Upper Saddle River, N.J.: Pearson Prentice Hall, 2007, xviii, 773. ISBN 9780131877153. info
  • DRYDEN, I. L. and K. V. MARDIA. Statistical shape analysis. Chichester: John Wiley & Sons, 1998, xvii, 347. ISBN 0471958166. info
Teaching methods
Class excercise, homework.
Assessment methods
The evaluation at the end of the semester will be in form of an oral exam on the subject matter studied during the semester. During the exam, the student's homework will also be evaluated.
Language of instruction
Czech
Follow-Up Courses
Further Comments
Study Materials
The course is taught annually.
The course is also listed under the following terms Spring 2015, Spring 2016, Spring 2017, spring 2018, Spring 2020, Spring 2021, autumn 2021, Autumn 2022, Autumn 2023, Autumn 2024.
  • Enrolment Statistics (Spring 2019, recent)
  • Permalink: https://is.muni.cz/course/sci/spring2019/Bi8773