DYNSTOCH

Statistical Methods for Dynamical Stochastic Models

In the period 2000 - 2004, Dynstoch was a research training network under the programme Improving Human Potential financed by the The Fifth Framework Programme of the European Commission. The research activities continue, and the network has been continued and expanded without EU funding. The web-site and the newsletter continue, and every year an annual workshop is held. Keep yourself informed about the activities by joining the DYNSTOCH mailing list.


Scientific co-ordinator: Frank van der Meulen and Mark Podolskij

The annual DYNSTOCH workshop

The DYNSTOCH workshop in 2025 will take place in Le Mans, 4 - 6 June. Conference website here

You can visit the past events here.

 

A list of past DYNSTOCH events
A list of past DYNSTOCH workshops
List of the young researchers employed under the Dynstoch contract in 2000 - 2004. 

 

 

Research

In many fields complex dynamical stochastic models are needed to describe processes that develop in time and/or space in a random way, usually with temporal or spatial interactions that are important for a proper understanding of the phenomenon under study and for making predictions about the system. A few concrete examples of such stochastic processes are: Interest rates, turbulent flows, communication in networks of neurons, and protein folding.


The high speed of present day computers has made use of complex stochastic models feasible, and at the same time, the important developments that have taken place in probability theory, in particular in the area of stochastic calculus, have only to a limited extent been used by statisticians to develop statistical methods for stochastic processes.


The principal aim of the DYNSTOCH network is to make a major contribution to the statistical theory and methodology for stochastic processes by taking advantage of the tools of modern probability theory including stochastic calculus and by using highly computer-intensive methods. This is partly done by modelling and statistical data analysis in a number of subject areas including neuro science, physiology, biology, turbulence (wind energy) and finance. 

 

The Original DYNSTOCH Teams:

Michael Sørensen 

Copenhagen University

Peter Spreij

University of Amsterdam

Uwe Küchler

HU Berlin

 Ernst Eberlein

University of Freiburg

Esko Valkeila

Valerie Isham

University College London

Andrea Gombani

IEIIT-CNR Padua

Jean Jacod 

Université Pierre et Marie Curie

 

The DYNSTOCH mailing list and newsletter

You can be kept informed about the activities of the network by joining the DYNSTOCH mailing list. The subscribers receive the DYNSTOCH Newsletter from time to time.

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