Zobrazeno 1 - 10
of 126
pro vyhledávání: '"van Lieshout, M. N. M."'
Autor:
Baki, Z., van Lieshout, M. N. M.
To monitor the seismic hazard in the Groningen gas field, we modify the rate-and-state model that relates changes in pore pressure to induced seismic hazard by allowing for noise in pore pressure measurements and by explicitly taking into account gas
Externí odkaz:
http://arxiv.org/abs/2403.13413
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 gradient-boosted regression trees (Chen & Guestrin, 2016) to the point p
Externí odkaz:
http://arxiv.org/abs/2401.17966
Previous approaches to modelling interval-censored data have often relied on assumptions of homogeneity in the sense that the censoring mechanism, the underlying distribution of occurrence times, or both, are assumed to be time-invariant. In this wor
Externí odkaz:
http://arxiv.org/abs/2401.17905
Autor:
van Lieshout, M. N. M.
We study a Markov decision problem in which the state space is the set of finite marked point configurations in the plane, the actions represent thinnings, the reward is proportional to the mark sum which is discounted over time, and the transitions
Externí odkaz:
http://arxiv.org/abs/2309.03752
Autor:
van Lieshout, M. N. M.
We propose a new fully non-parametric two-step adaptive bandwidth selection method for kernel estimators of spatial point process intensity functions based on the Campbell-Mecke formula and Abramson's square root law. We present a simulation study to
Externí odkaz:
http://arxiv.org/abs/2210.11902
Autor:
van Lieshout, M. N. M., Lu, C.
This paper discusses infill asymptotics for logistic regression estimators for spatio-temporal point processes whose intensity functions are of log-linear form. We establish strong consistency and asymptotic normality for the parameters of a Poisson
Externí odkaz:
http://arxiv.org/abs/2208.12080
Autor:
van Lieshout, M. N. M., Baki, Z.
The discovery of gas in Groningen in 1959 has been a massive boon to the Dutch economy. From the 1990s onwards though, gas production has led to induced seismicity. In this paper, we carry out a comprehensive exploratory analysis of the spatio-tempor
Externí odkaz:
http://arxiv.org/abs/2209.02386
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 develop a combined machine learning and statistical modeling process to pr
Externí odkaz:
http://arxiv.org/abs/2112.07257
Aoristic data can be described by a marked point process in time in which the points cannot be observed directly but are known to lie in observable intervals, the marks. We consider Bayesian state estimation for the latent points when the marks are m
Externí odkaz:
http://arxiv.org/abs/2108.10584