New research project about statistical inference
The Independent Research Fund Denmark (DFF) supports the development of new robust statistical methods for analyzing large and complex volumes of data. Professor Susanne Ditlevsen is to lead the four-year research project.
DFF | Natural Sciences has allocated DKK 2.5 million for the research project "Statistical inference for Coupled Stochastic Processes". This will include funding a PhD student for the next four years; the vacant position has just been announced.
Susanne describes the project as follows:
“The statistical problem of parameter estimation in partially observed multidimensional nonlinear stochastic processes with different time scales is an open problem.
Modern empirical methods hugely increase the amount and type of data we collect, and the importance of complex models is increasing. The project goal is to find more principled ways of statistical inference in this type of models by hybrid methods.
The hypothesis is that by splitting the model into a part where maximum likelihood estimation is available, a non-linear stochastic part where sophisticated methods can be applied, and a deterministic part, which can be propagated according to the specified dynamics, a large estimation problem can be split into smaller estimation problems.
This is expected to lead to more robust and computationally efficient statistical inference. In particular, approximations are only implemented where necessary and the computational intensive methods only used where it is needed.”
Independent Research Fund Denmark | Natural Sciences allocates research grants to researchers working within natural sciences, computer science and mathematics with a cognition-related, but not necessarily practical aim.
Statistical inference for Coupled Stochastic Processes with multiple timescales
01-01-2020 - 28-02-2024
DKK 2.564.848 from Independent Research Fund Denmark