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Dependence Modelling using Vine Copulas: Theory and Applications 5 Credits

Course Contents

The course starts with a background chapter on multivariate and conditional distributions
and copulas. This includes the parametric classes of elliptical, Archimedean and extreme value copulas. Their
parameter estimation and graphical tools for the identification of sensible bivariate copula models to
data are presented. The decomposition and construction principle of drawable (D-), canonical (C-) and
regular (R-) vines is developed and discussed. The course concludes with recent extensions of vines
including advances in estimation, model selection, for special data structures and reviews major applications
in finance, life and earth sciences, insurance and engineering. It also provides an overview of the available
software, in particular R, to select, estimate and visualize vinebased models.

Prerequisites

Admitted to a doctoral program in statistics or a related subject of a recognized business school or
university.

Level of Education: XXX
Course code/Ladok code: FJDMV30
The course is conducted at: Jönköping International Business School

Previous and ongoing course occasions

Type of course
FORS
Study type
Campus
Semester
Autumn 2020: Aug 24 - Nov 08
Rate of Study
33%
Language
English
Location
Jönköping
Time
Day
Syllabus
HTML  PDF
Application code
HJ-FJ036
Last modified 2020-09-21 11:34:47

Content updated 2020-08-25