Continuous‐Time Causal Inference With Marked Point Process Weights: An Example on Sodium‐Glucose Co‐Transporters 2 Inhibitor Medications and Urinary Tract Infection
Sign Up to like & getrecommendations! Published in 2025 at "Statistics in Medicine"
DOI: 10.1002/sim.70102
Abstract: Treatment‐confounder feedback is present in time‐to‐recurrent or longitudinal event analysis when time‐dependent confounders are themselves influenced by previous treatments. Conventional models produce misleading statistical inference of causal effects due to conditioning on these factors on… read more here.
Keywords: continuous time; point process; time; marked point ... See more keywords
A numerical method for computing interval distributions for an inhomogeneous Poisson point process modified by random dead times
Sign Up to like & getrecommendations! Published in 2021 at "Biological Cybernetics"
DOI: 10.1007/s00422-021-00868-8
Abstract: The inhomogeneous Poisson point process is a common model for time series of discrete, stochastic events. When an event from a point process is detected, it may trigger a random dead time in the detector,… read more here.
Keywords: poisson point; point process; process; point ... See more keywords
A Model Based Poisson Point Process for Downlink Cellular Networks Using Joint Scheduling
Sign Up to like & getrecommendations! Published in 2019 at "Wireless Personal Communications"
DOI: 10.1007/s11277-019-06353-7
Abstract: This paper proposes a model based on a random cellular network to analyse performance of Joint Scheduling in which a typical user measures signal-to-interference-plus-noise ratio (SINR) on different resource blocks from K nearest BSs in… read more here.
Keywords: using joint; joint scheduling; model based; point process ... See more keywords
Martingale representation in the enlargement of the filtration generated by a point process
Sign Up to like & getrecommendations! Published in 2021 at "Stochastic Processes and their Applications"
DOI: 10.1016/j.spa.2020.09.008
Abstract: Let $X$ be a point process and let $\mathbb{X}$ denote the filtration generated by $X$. In this paper we study martingale representation theorems in the filtration $\mathbb{G}$ obtained as an initial and progressive enlargement of… read more here.
Keywords: point process; process; filtration generated; enlargement ... See more keywords
Self-exciting point process models for political conflict forecasting
Sign Up to like & getrecommendations! Published in 2017 at "European Journal of Applied Mathematics"
DOI: 10.1017/s095679251700033x
Abstract: In 2008, the Defense Advanced Research Project Agency commissioned a database known as the Integrated Crisis Early Warning System to serve as the foundation for models capable of detecting and predicting increases in political conflict… read more here.
Keywords: conflict; point process; political conflict; self exciting ... See more keywords
A point process model for generating biofilms with realistic microstructure and rheology
Sign Up to like & getrecommendations! Published in 2018 at "European Journal of Applied Mathematics"
DOI: 10.1017/s0956792518000220
Abstract: Biofilms are communities of bacteria that exhibit a multitude of multiscale biomechanical behaviours. Recent experimental advances have led to characterisations of these behaviours in terms of measurements of the viscoelastic moduli of biofilms grown in… read more here.
Keywords: point process; model; rheology; mechanical properties ... See more keywords
The integrated nested Laplace approximation applied to spatial log-Gaussian Cox process models
Sign Up to like & getrecommendations! Published in 2022 at "Journal of Applied Statistics"
DOI: 10.1080/02664763.2021.2023116
Abstract: Spatial point process models are theoretically useful for mapping discrete events, such as plant or animal presence, across space; however, the computational complexity of fitting these models is often a barrier to their practical use.… read more here.
Keywords: point process; log gaussian; process models; cox process ... See more keywords
XGBoostPP: Tree-based Estimation of Point Process Intensity Functions
Sign Up to like & getrecommendations! Published in 2024 at "Journal of Computational and Graphical Statistics"
DOI: 10.1080/10618600.2025.2520582
Abstract: 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… read more here.
Keywords: point process; intensity; point; tree based ... See more keywords
Predicting urban signal-controlled intersection congestion events using spatio-temporal neural point process
Sign Up to like & getrecommendations! Published in 2024 at "International Journal of Digital Earth"
DOI: 10.1080/17538947.2024.2376270
Abstract: ABSTRACT The urban traffic signal-controlled intersections are of great significance for solving the problem of urban road congestion. Previous research on congestion prediction mainly aggregated data at the level of road segments or traffic flow… read more here.
Keywords: congestion; point process; congestion events; signal controlled ... See more keywords
Marked point process representation of oscillatory dynamics underlying working memory
Sign Up to like & getrecommendations! Published in 2020 at "Journal of Neural Engineering"
DOI: 10.1088/1741-2552/abd577
Abstract: Objective. Computational models of neural activity at the meso-scale suggest the involvement of discrete oscillatory bursts as constructs of cognitive processing during behavioral tasks. Classical signal processing techniques that attempt to infer neural correlates of… read more here.
Keywords: oscillatory dynamics; point process; process; memory ... See more keywords
Nonlinear point-process estimation of neural spiking activity based on variational Bayesian inference
Sign Up to like & getrecommendations! Published in 2022 at "Journal of Neural Engineering"
DOI: 10.1088/1741-2552/ac88a0
Abstract: Objective. Understanding neural encoding and decoding processes are crucial to the development of brain-machine interfaces (BMI). Higher decoding speed of neural signals is required for the large-scale neural data and the extremely low detection delay… read more here.
Keywords: based variational; nonlinear point; point process; bayesian inference ... See more keywords