Bayesian inference for discretely observed diffusion processes
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The goal of this doctoral project was to develop, justify and implement Bayesian procedures for discretely observed diffusion processes. In the remainder of this introduction we will explore the concepts of diusion processes and Bayesian inference for discretely observed data a bit more and then give the reader a taste of some ideas which will be of importance later on. A thorough treatment of the underlying theory can for example be found in the monograph on inference for stochastic processes by Liptser and Shiryaev (2001).
Moritz Schauer was born on the 15th of April 1980 in Marburg, Germany. After obtaining his Abitur at the Martin-Luther-Schule in Marburg he studied Mathematical Economics at the Technical University Dresden from 2000 on. After he received the Vordiplom in Mathematical Economics
in 2003 he went to explore a particular part of the southern hemisphere and took up again his studies in 2004 at the University of Hamburg where he joined the Master programme on Stochastic Processes. There he wrote his thesis on stochastic monotonicity and association of diusion processes under supervision of Prof. H. Daduna and obtained his title Diplom-Mathematiker in 2009. From 2010 to 2014 he worked in Delft on the project “Bayesian nonparametrics for diusion processes,” funded by the STAR cluster of the Dutch Science Foundation NWO and the Delft University of Technology promoted by Dr. ir. F.H. van der Meulen, Prof. dr. J.H. Van Zanten and Prof. dr. ir. G. Jongbloed.