Ottmar Cronie
I am a mathematical statistician and my research is primarily in spatial and spatio-temporal statistics as well as statistical learning. The emphasis of my research is in point processes, which have classically been considered as a part of stochastic geometry and can most easily be described as generalised random samples where dependencies and random sample sizes are allowed - this is exactly what makes them particularly suitable for modelling events in space and/or time. At present, the main focus is on the further development of a new theory for statistical learning for point processes that I have recently developed. The applied part of my research focuses mainly on epidemiology where the main focus at the moment is research on covid-19 and mosquito-borne diseases - this research is conducted in collaboration with, among others, the research group of Annika Rosengren (GU) and Max Petzold and Laith Hussain (GU).
Showing 29 publications
A cross-validation-based statistical theory for point processes
Hierarchical spatio-temporal change-point detection
Local inhomogeneous weighted summary statistics for marked point processes
BMI, sex and outcomes in hospitalised patients in western Sweden during the COVID-19 pandemic
Severe COVID-19 in people 55 and older during the first year of the pandemic in Sweden
Spatio-temporal point patterns on linear networks: Pseudo-separable intensity estimation
Inhomogeneous higher-order summary statistics for point processes on linear networks
Resample-smoothing of Voronoi intensity estimators
The exceptional 2018 European water seesaw calls for action on adaptation
Concurrent climate extremes in the key wheat producing regions of the world
Adaptive algorithm for sparse signal recovery
Summary statistics for inhomogeneous marked point processes
Spatio-temporal point process statistics: a review
J-function for inhomogeneous spatio-temporal point processes
Spatiotemporal Modeling of Swedish Scots Pine Stands
Some edge correction methods for marked spatio-temporal point process models
Modelling and Inference for Spatio-Temporal Marked Point Processes
Different Aspects of Inference for Spatio-Temporal Point Processes
Maximum likelihood estimation in a discretely observed immigration-death process
Some edge correction methods for marked spatio-temporal point process models
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