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Simulation of nonhomogeneous poisson processes by thinning

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  1. Sobin Joseph & Shashi Jain, 2023. "A neural network based model for multi-dimensional nonlinear Hawkes processes," Papers 2303.03073, arXiv.org.
  2. Robert T. Holden, 1985. "Failure Time Models for Thinned Crime Commission Data," Sociological Methods & Research, , vol. 14(1), pages 3-30, August.
  3. Sidorov, Sergei & Mironov, Sergei, 2021. "Growth network models with random number of attached links," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 576(C).
  4. Jie Chen & Joseph Glaz, 2016. "Multiple Window Scan Statistics for Two Dimensional Poisson Processes," Methodology and Computing in Applied Probability, Springer, vol. 18(4), pages 967-977, December.
  5. Giesecke, K. & Schwenkler, G., 2019. "Simulated likelihood estimators for discretely observed jump–diffusions," Journal of Econometrics, Elsevier, vol. 213(2), pages 297-320.
  6. Julio A. Crego, 2017. "Short Selling Ban and Intraday Dynamics," Working Papers wp2017_1715, CEMFI.
  7. Mohammadi, M. & Rezakhah, S. & Modarresi, N., 2020. "Semi-Lévy driven continuous-time GARCH process," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 557(C).
  8. Lamprinakou, Stamatina & Barahona, Mauricio & Flaxman, Seth & Filippi, Sarah & Gandy, Axel & McCoy, Emma J., 2023. "BART-based inference for Poisson processes," Computational Statistics & Data Analysis, Elsevier, vol. 180(C).
  9. Collin Drent & Melvin Drent & Joachim Arts, 2024. "Condition-Based Production for Stochastically Deteriorating Systems: Optimal Policies and Learning," Manufacturing & Service Operations Management, INFORMS, vol. 26(3), pages 1137-1156, May.
  10. Canyakmaz, Caner & Özekici, Süleyman & Karaesmen, Fikri, 2019. "An inventory model where customer demand is dependent on a stochastic price process," International Journal of Production Economics, Elsevier, vol. 212(C), pages 139-152.
  11. Xin-Yu Tian & Xincheng Shi & Cheng Peng & Xiao-Jian Yi, 2021. "A Reliability Growth Process Model with Time-Varying Covariates and Its Application," Mathematics, MDPI, vol. 9(8), pages 1-15, April.
  12. Cavaliere, Giuseppe & Lu, Ye & Rahbek, Anders & Stærk-Østergaard, Jacob, 2023. "Bootstrap inference for Hawkes and general point processes," Journal of Econometrics, Elsevier, vol. 235(1), pages 133-165.
  13. G. Avlogiaris & A. C. Micheas & K. Zografos, 2019. "A Criterion for Local Model Selection," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 81(2), pages 406-444, December.
  14. Christoph Zechner & Heinz Koeppl, 2014. "Uncoupled Analysis of Stochastic Reaction Networks in Fluctuating Environments," PLOS Computational Biology, Public Library of Science, vol. 10(12), pages 1-9, December.
  15. Andreia Monteiro & Raquel Menezes & Maria Eduarda Silva, 2021. "Modelling informative time points: an evolutionary process approach," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 30(2), pages 364-382, June.
  16. Dassios, Angelos & Zhao, Hongbiao, 2017. "Efficient simulation of clustering jumps with CIR intensity," LSE Research Online Documents on Economics 74205, London School of Economics and Political Science, LSE Library.
  17. Julio A. Crego, 2017. "Short Selling Ban and Intraday Dynamics," Working Papers wp2018_1715, CEMFI.
  18. Achini Wellalage & Mark Fackrell & Lele Zhang, 2024. "A Monte Carlo simulation-based simulated annealing algorithm for predicting the minimum staffing requirement at a blood donor centre," Annals of Operations Research, Springer, vol. 342(3), pages 1945-1990, November.
  19. Mat'uv{s} Maciak & Ostap Okhrin & Michal Pev{s}ta, 2019. "Infinitely Stochastic Micro Forecasting," Papers 1908.10636, arXiv.org, revised Sep 2019.
  20. Huh, Woonghee Tim & Lee, Jaywon & Park, Heesang & Park, Kun Soo, 2019. "The potty parity problem: Towards gender equality at restrooms in business facilities," Socio-Economic Planning Sciences, Elsevier, vol. 68(C).
  21. Swishchuk, Anatoliy & Zagst, Rudi & Zeller, Gabriela, 2021. "Hawkes processes in insurance: Risk model, application to empirical data and optimal investment," Insurance: Mathematics and Economics, Elsevier, vol. 101(PA), pages 107-124.
  22. Rodrigo Saul Gaitan & Keh‐Shin Lii, 2021. "On the Estimation of Periodicity or Almost Periodicity in Inhomogeneous Gamma Point‐Process Data," Journal of Time Series Analysis, Wiley Blackwell, vol. 42(5-6), pages 711-736, September.
  23. Li, Dongmin & Hu, Qingpei & Wang, Lujia & Yu, Dan, 2019. "Statistical inference for Mt/G/Infinity queueing systems under incomplete observations," European Journal of Operational Research, Elsevier, vol. 279(3), pages 882-901.
  24. Xiaoting Li & Christian Genest & Jonathan Jalbert, 2021. "A self‐exciting marked point process model for drought analysis," Environmetrics, John Wiley & Sons, Ltd., vol. 32(8), December.
  25. Angelos Dassios & Hongbiao Zhao, 2017. "Efficient Simulation of Clustering Jumps with CIR Intensity," Operations Research, INFORMS, vol. 65(6), pages 1494-1515, December.
  26. Buckwar, Evelyn & Meddah, Amira, 2025. "Numerical approximations and convergence analysis of piecewise diffusion Markov processes, with application to glioma cell migration," Applied Mathematics and Computation, Elsevier, vol. 491(C).
  27. Kyungsub Lee, 2023. "Multi-kernel property in high-frequency price dynamics under Hawkes model," Papers 2302.11822, arXiv.org.
  28. Gao, Lisa & Shi, Peng, 2022. "Leveraging high-resolution weather information to predict hail damage claims: A spatial point process for replicated point patterns," Insurance: Mathematics and Economics, Elsevier, vol. 107(C), pages 161-179.
  29. Hermann, Simone & Ickstadt, Katja & Müller, Christine H., 2018. "Bayesian prediction for a jump diffusion process – With application to crack growth in fatigue experiments," Reliability Engineering and System Safety, Elsevier, vol. 179(C), pages 83-96.
  30. Lu Shaochuan, 2023. "Scalable Bayesian Multiple Changepoint Detection via Auxiliary Uniformisation," International Statistical Review, International Statistical Institute, vol. 91(1), pages 88-113, April.
  31. R. Guo & C. E. Love, 1994. "Simulating nonhomogeneous poisson processes with proportional intensities," Naval Research Logistics (NRL), John Wiley & Sons, vol. 41(4), pages 507-522, June.
  32. Frederic Paik Schoenberg & Marc Hoffmann & Ryan J. Harrigan, 2019. "A recursive point process model for infectious diseases," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 71(5), pages 1271-1287, October.
  33. Ji, Jingru & Wang, Donghua & Xu, Dinghai & Xu, Chi, 2020. "Combining a self-exciting point process with the truncated generalized Pareto distribution: An extreme risk analysis under price limits," Journal of Empirical Finance, Elsevier, vol. 57(C), pages 52-70.
  34. Ran Liu & Michael E. Kuhl & Yunan Liu & James R. Wilson, 2019. "Modeling and Simulation of Nonstationary Non-Poisson Arrival Processes," INFORMS Journal on Computing, INFORMS, vol. 31(2), pages 347-366, April.
  35. Ivan Jericevich & Dharmesh Sing & Tim Gebbie, 2021. "CoinTossX: An open-source low-latency high-throughput matching engine," Papers 2102.10925, arXiv.org.
  36. Abhinav Garg & Naman Shukla & Lavanya Marla & Sriram Somanchi, 2021. "Distribution Shift in Airline Customer Behavior during COVID-19," Papers 2111.14938, arXiv.org, revised Dec 2021.
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