SubjectsSubjects(version: 964)
Course, academic year 2024/2025
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Specialized seminar in probability and mathematical statistics - NMSA601
Title: Oborový seminář z pravděpodobnosti a matematické statistiky
Guaranteed by: Department of Probability and Mathematical Statistics (32-KPMS)
Faculty: Faculty of Mathematics and Physics
Actual: from 2024
Semester: both
E-Credits: 2
Hours per week, examination: 0/2, C [HT]
Capacity: unlimited
Min. number of students: unlimited
4EU+: no
Virtual mobility / capacity: no
State of the course: taught
Language: Czech, English
Teaching methods: full-time
Note: you can enroll for the course repeatedly
you can enroll for the course in winter and in summer semester
Guarantor: doc. RNDr. Daniel Hlubinka, Ph.D.
prof. RNDr. Bohdan Maslowski, DrSc.
Teacher(s): doc. RNDr. Daniel Hlubinka, Ph.D.
prof. RNDr. Bohdan Maslowski, DrSc.
prof. RNDr. Ivan Mizera, CSc.
Class: Pravděp. a statistika, ekonometrie a fin. mat.
Classification: Mathematics > Probability and Statistics
Is interchangeable with: NSTP135
Annotation -
Specialized seminar situated on the border of probability and modern statistical inference, extending the knowledge of PhD students towards the world level. The key subjects are empirical processes and their strong approximations; invariance principles on various topological spaces; functional data (e.g. processes), and inference on parameters from various functional spaces; transformations of data, characterizations of probability distributions. Besides these subjects, we shall regularly follow important new results and methods. There will be a space for students' problems of interest.
Last update: T_KPMS (06.05.2014)
Aim of the course -

Specialized subject seminar, extending the knowledge of PhD students toward the respected level, on the border of probability and modern statistical inference. The keyward subjects are: empirical processes; differentiable statistical functionals; invariance principles; functional data (e.g. processes), and the inference on their parameters; emphasis on testing statistical hypotheses, including nonparametric, mainly concerning the mutlivariate datasets. Besides that, we shall follow the progress in the area in the world literature.

Last update: Jurečková Jana, prof. RNDr., DrSc. (25.09.2020)
Course completion requirements -

The seminar is concluded with a mark, either pass/fail. The mark is given for the presentations delivered by the student during the seminar on the basis of independent study of the recommended literature, as well as active participation in the sessions.

Last update: Swart Jan, Dr. (18.02.2021)
Literature -

Terence Tao: Topics in random matrix theory

https://terrytao.files.wordpress.com/2011/02/matrix-book.pdf

Last update: Swart Jan, Dr. (19.02.2024)
Teaching methods -

Presentations and discussions between the participants. The seminar will until further notice take place online via Zoom. Individual consultations are possible.

Last update: Swart Jan, Dr. (18.02.2021)
 
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