Research

Jump to Book Chapters, Conference Proceedings or Working Papers. Peer-reviewed journal articles Gellert, K. & Schlögl, E. 2021, ‘Parameter Learning and Change Detection Using a Particle Filter with Accelerated Adaptation’, Risks, 9(12). View/Download from: Publisher’s site (open access)/Working paper version on SSRN Click arrow to view description This paper presents the construction of a particle filter, which incorporates elements inspired by genetic algorithms, in order to achieve accelerated adaptation of the estimated posterior distribution to changes in model parameters.