Syllabus

Title
5845 Advanced Topics in Dependence Modeling
Instructors
Univ.Prof. Dr. Johana Genest Neslehova
Contact details
Type
PI
Weekly hours
2
Language of instruction
Englisch
Registration
02/19/24 to 03/01/24
Registration via LPIS
Notes to the course
Dates
Day Date Time Room
Monday 04/08/24 10:00 AM - 01:00 PM TC.5.28
Tuesday 04/09/24 10:00 AM - 01:00 PM D2.0.031 Workstation-Raum
Wednesday 04/10/24 10:00 AM - 01:00 PM D2.0.031 Workstation-Raum
Thursday 04/11/24 10:00 AM - 01:00 PM D2.0.031 Workstation-Raum
Friday 04/12/24 10:00 AM - 01:00 PM D2.0.031 Workstation-Raum
Thursday 06/20/24 10:00 AM - 01:00 PM Online-Einheit
Friday 06/21/24 10:00 AM - 01:00 PM Online-Einheit
Contents
This course will cover advanced topics in dependence modeling with copulas. After a brief review of copulas and copula models and statistical inference for such models in the bivariate case, the course will focus on copula modeling in higher dimensions, notably vine copula constructions, hierarchical models and factor copulas. We will also explore copula models for time series and the intricacies of copula modeling of discrete data and more generally of data with ties.
 
Assessment: 
 
The course assessment will be based on project work and on an oral presentation of the project.
 
Suggested reading:
 
  • An Introduction to Copulas by R. Nelsen, Springer 2007 (general reference for review of copulas and copula models)
  • Elements of Copula Modeling with R by M. Hofert, I. Kojadinovic, M. Mächler and J. Yan, Springer 2018 (general reference for review of inference for copula models)
  • Dependence Modeling with Copulas by H. Joe, CRC Press, Boca Raton, FL 2015
  • Analyzing Dependent Data with Vine Copulas by C. Czado, Springer 2019
  • Vine Copula Based Modeling by C. Czado and T. Nagler, Annu. Rev. Stat. Appl. 2022. 9:453–77

 

 

 

Learning outcomes

Students will acquire a good understanding of theoretical and practical aspects of modeling dependent multivariate data with copulas. Moreover, they will be able to analyze data and use these models with R.

Attendance requirements

at least 80% of the units

Teaching/learning method(s)

Classroom teaching; project and group work

Assessment

The course assessment will be based on project work and on an oral presentation of the project.

Readings

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Recommended previous knowledge and skills

This course builds up on the course "Dependence Modeling with Copulas" that I taught in the Winter Semester 2023/24. However, the first lecture will review the concepts and tools from the latter course that will be needed, so it is not necessary that students followed the course in the previous term. Still, some knowledge of copulas and copula models is welcome, albeit elementary.

Last edited: 2024-01-17



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