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Published in 2021 at "Environmetrics"
DOI: 10.1002/env.2697
Abstract: A self‐exciting marked point process approach is proposed to model clustered low‐flow events. It combines a self‐exciting ground process designed to capture the temporal clustering behavior of extreme values and an extended Generalized Pareto mark… read more here.
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Published in 2018 at "Applied Mathematical Modelling"
DOI: 10.1016/j.apm.2018.01.003
Abstract: Abstract To better describe the characteristics of time series of counts such as over-dispersion, asymmetry and structural change, this paper considers a class of integer-valued self-exciting threshold autoregressive processes that properly capture flexible asymmetric and… read more here.
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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.
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Published in 2025 at "Journal of Applied Statistics"
DOI: 10.1080/02664763.2025.2459245
Abstract: The paper first highlights important drawbacks and biases related to the common use of time-rescaling to assess the goodness-of-fit (Gof) of self-exciting temporal point process (SETPP) models. Then it presents a new predictive time-rescaling approach… read more here.
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Published in 2024 at "Quantitative Finance"
DOI: 10.1080/14697688.2025.2488450
Abstract: We investigate the optimal reinsurance problem in a risk model with jump clustering features. This modeling framework is inspired by the concept initially proposed in Dassios and Zhao (2011), combining Hawkes and Cox processes with… read more here.
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Published in 2019 at "IEEE Access"
DOI: 10.1109/access.2019.2900340
Abstract: In this paper, a nonparametric spatial-temporal self-exciting point process is proposed to model clustering features in emergency calls. Gaussian kernel density functions are considered. The expectation-maximization algorithm is adopted for estimating the model. A simulation… read more here.
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Published in 2025 at "BMC Infectious Diseases"
DOI: 10.1186/s12879-025-11506-0
Abstract: Rift Valley fever (RVF) is a mosquito-borne zoonotic disease for which predictive modeling is often hindered by sparse data, particularly the high frequency of zero counts in both human and livestock surveillance systems. While zero-inflated… read more here.
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Published in 2018 at "Statistical Science"
DOI: 10.1214/18-sts652
Abstract: This is an excellent and extremely well-written summary of recent research on self-exciting spatialtemporal point processes. It contributes very nicely to the literature and I will use it personally to teach my graduate students about… read more here.
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Published in 2024 at "INFORMS Journal on Computing"
DOI: 10.1287/ijoc.2022.0351.cd
Abstract: This directory contains the code for the Clustering then Estimation of Spatio-Temporal Self-Exciting Processes (CTE) algorithm. read more here.