FG 1735/1: Identifiability and structural inference for high-dimensional diffusion matrices in DFG FG 1735

We will develop theory and an estimation methodology for the analysis of sparsely parametrised high-dimensional diffusion matrices, including in particular identifiability issues. This requires the combination of adaptive smoothing techniques and sparsity inducing penalization methods and results in a challenging simultaneous adaptation problem. The analysis is supposed to provide more fundamental insight even for more classical situations for independent and identically distributed data.

Reiß, Markus Prof. Dr. (Details) (Forschergruppen (DFG))

Projektstart: 04/2012
Projektende: 03/2015

Zuletzt aktualisiert 2020-11-03 um 23:19