5 citations · 22 across the 11 of their papers we have counts for
5 papers · 1 filter
XGBoostPP: Tree-based Estimation of Point Process Intensity Functions
C. Lu, Y. Guan, M. N. M. van Lieshout +1
We propose a novel tree-based ensemble method, named XGBoostPP, to nonparametrically estimate the intensity of a point process as a function of covariates. It extends the use of gr…
Data-driven chimney fire risk prediction using machine learning and point process tools
C. Lu, M. N. M. van Lieshout, M. de Graaf +1
Chimney fires constitute one of the most commonly occurring fire types. Precise prediction and prompt prevention are crucial in reducing the harm they cause. In this paper, we deve…
A multi-scale area-interaction model for spatio-temporal point patterns
A. Iftimi, M. N. M. van Lieshout, F. Montes
Models for fitting spatio-temporal point processes should incorporate spatio-temporal inhomogeneity and allow for different types of interaction between points (clustering or regul…
Bandwidth selection for kernel estimators of the spatial intensity function
O. Cronie, M. N. M. van Lieshout
We discuss and compare various approaches to the problem of bandwidth selection for kernel estimators of intensity functions of spatial point processes. We also propose a new metho…
A J-function for inhomogeneous point processes
M. N. M. van Lieshout
We propose new summary statistics for intensity-reweighted moment stationary point processes that generalise the well known J-, empty space, and nearest-neighbour distance distribu…