Preprints and Forthcoming Papers
- M N M van Lieshout,
Stochastic geometry models in image analysis and spatial
statistics,
CWI tract 108, 1995.
- O Barndorff-Nielsen, W S Kendall, and M N M van Lieshout (Eds.)
Stochastic geometry, likelihood and computation,
Chapman and Hall/CRC Press, 1999.
- M N M van Lieshout,
Markov point processes and their applications,
Imperial College Press, 2000.
- L Florack, R Duits, G Jongbloed, M-C van Lieshout and L Davies (Eds.),
Mathematical methods for signal analysis and representation,
Springer, 2012.
- M N M van Lieshout.
Theory of spatial statistics: A concise introduction.
Chapman and Hall/CRC Press, 2019.
- M N M van Lieshout and Z Baki.
Exploring seismic hazard in the Groningen gas field using adaptive
kernel smoothing.
ArXiv 2209.02386, August 2022.
Mathematical Geosciences, to appear.
- M N M van Lieshout and C Lu.
Infill asymptotics for logistic regression estimators for
spatio-temporal point processes.
ArXiv 2208.12080, August 2022.
- M N M van Lieshout.
Optimal decision rules for marked point process models.
Arxiv 2309.03752, September 2023.
- M N M van Lieshout and C Lu.
Contribution to the Discussion of "Automatic Change-Point Detection in
Time Series via Deep Learning" by Li, Fearnhead, Fryzlewics and Wang.
Journal of the Royal Statistical Society, to appear.
- M N M van Lieshout.
Contribution to the Discussion of "Marked Spatial Point Processes: Current State
and Extensions to Point Processes on Linear Networks" by Eckardt and Moradi.
Journal of Agricultural, Biological and Environmental Statistics, to appear.
- M N M van Lieshout and R L Markwitz.
A non-homogeneous semi-Markov model for interval censoring.
Arxiv 2401.17905, January 2024.
- C Lu, Y Guan, M N M van Lieshout and G Xu.
XGBoostPP: Tree-based estimation of point process intensity functions.
Arxiv 2401.17966, January 2024.
- Z Baki and M N M van Lieshout.
On the moments of Cox rate-and-state models.
Arxiv 2403.13413, March 2024.
Marie-Colette van Lieshout
March 2024