MU11185 Applied Statistics II

Mathematical Institute in Opava
Summer 2024
Extent and Intensity
2/1/0. 3 credit(s). Type of Completion: zk (examination).
Teacher(s)
RNDr. Jaroslav Bradík (lecturer)
RNDr. Jaroslav Bradík (seminar tutor)
Guaranteed by
RNDr. Oldřich Stolín, Ph.D.
Mathematical Institute in Opava
Timetable
Mon 14:45–16:20 LVT1
  • Timetable of Seminar Groups:
MU11185/01: Mon 16:25–17:10 LVT1, J. Bradík
Prerequisites
( MU20027 Applied Statistics I || MU11160 Applied Statistics ) && TYP_STUDIA(B)
The student is supposed to be acquainted with the material covered in Applied statistics.
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 course Applied Statistics consists of lectures and tutorials whose goal is to introduce students to Bayesian statistics and its practical methods.
Syllabus
1. Statistical models.
2. The geometry of the space of probability distributions.
3. Singular statistical models.
4. Variational Bayesian methods.
5. Hierarchical models
6. Pseudo-Bayesian methods: Expectation-maximization algorithm. Empirical Bayesian methods.
7. First encounter with stochastic differential equations.
8. Kalman filters.
9. Dynamic filters.
10. Purposeful control under random influences.
Literature
    required literature
  • Christian P. Robert. The Bayesian choice: From decision-theoretic foundations to computational implementation. New York, 2007. info
    recommended literature
  • Sumio Watanabe. Algebraic geometry and statistical learning theory. New York, 2009. ISBN 9780521864671. info
  • Amari, Shun-ichi and Nagaoka, Hiroshi. Methods of Information Geometry. Oxford University Press, AMS, 2007. info
  • Christian P. Robert and George Casella. Monte Carlo statistical methods. New York, 2004. info
    not specified
  • Karl Friston and Klaas Stephan and Baojuan Li and Jean Daunizeau. Generalised Filtering, Mathematical Problems in Engineering, Article ID 621670. 2010. info
Language of instruction
Czech
Further comments (probably available only in Czech)
Study Materials
The course can also be completed outside the examination period.
Teacher's information
Requirements to pass the course:
Satisfactory completion of all assigned exercises with at most two exceptions.
Activity Difficulty [h]
Cvičení 10
Domácí příprava na výuku 24
Přednáška 20
Příprava na zápočet 8
Příprava na zkoušku 16
Summary 78
The course is also listed under the following terms Summer 2021, Summer 2022, Summer 2023.
  • Enrolment Statistics (recent)
  • Permalink: https://is.slu.cz/course/sumu/summer2024/MU11185