Seminar on Statistics and Risk Management

The seminar is organised by the chair of Mathematical Statistics. The speakers in this seminar are Master students who present the results of their Master Thesis, PhD students of the chair who speak about their current researsch as well as external researchers in the area of statistics.

If not stated otherwise, the seminar starts at 12:15 and takes place in room BC1 2.01.10.

 

 

11.03.2019

A simple non-parametric goodness-of-fit test for elliptical copula

Stephan Haug, 13 March 2019. Please note, the talk will start at 13:15[more]

Category: Seminar "Statistics and Risk Management", Vortrag

28.02.2019

Parameter estimation for time series models based on the simulated characteristic function (copy 1)

Thiago do Rego Sousa, 13 March 2019. Please note, the talk will start at 14:00[more]

Category: Seminar "Statistics and Risk Management", Vortrag

27.11.2018

General vine copula models for stationary multivariate time series

Daniel Krüger, 12 December 2018. Please note, the talk will take place in room BC1 2.01.11[more]

Category: Seminar "Statistics and Risk Management", Vortrag

09.10.2018

Value at risk estimation with subset simulation

Raphael Weber, 24 October 2018. Please note, the talk will start at 12:30[more]

Category: Seminar "Statistics and Risk Management", Vortrag

04.07.2018

Bayesian non-parametric conditional copula estimation, with application to twin data

Dr. Luciana Dalla Valle (University of Plymouth, UK), 11 July 2018[more]

Category: Seminar "Statistics and Risk Management", Vortrag

17.06.2018

Statistical methods for the objective assessment of subjective ratings of advanced driver assistance systems

Elias Jebabli, Friday, 28 June 2018. Please note, the talk will start at 15:00[more]

Category: Seminar "Statistics and Risk Management", Vortrag

15.06.2018

Regular vine based quantile regression

Jakob Herrmann, Friday, 28 June 2018. Please note, the talk will start at 14:00[more]

Category: Seminar "Statistics and Risk Management", Vortrag

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