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163-176

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- Faculty of Mathematics and Natural Sciences, Universitas Padjadjaran, Indonesia

author

- Faculty of Mathematics and Natural Sciences, Universitas Padjadjaran, Indonesia

author

- Department of Mathematics, Faculty of Mathematics and Natural Science, Universitas Padjadajran, Indonesia

author

- Department of Marine Sciences, Faculty of Fishery and Marine Sciences, Universitas Padjadjaran, Indonesia

References

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- [3] K. K. Kataria and P. Vellaisamy, Saigo space-time fractional Poisson process via Adomian decomposition method. Stat. Probab. Lett. vol. 129, pp. 69-80, 2017.
- [4] I. Eliazar, The Poisson aggregation process. Chaos, Solitons Fractals, vol. 83, pp. 38-53, 2016.
- [5] A. Cholaquidis, L. Forzani, P. Llop, and L. Moreno, On the classification problem for Poisson point processes. J. Multivar. Anal., vol. 153, pp. 1–15, 2017.
- [6] M. Fu and X. Peng, On the sample path properties of mixed Poisson processes. Oper. Res. Lett., vol. 46, pp. 1-6, 2018.
- [7] L. Vicini, L. K. Hotta, and J. A. Achcar, Non-Homogeneous Poisson Processes Applied to Count Data: A Bayesian Approach Considering Different Prior Distributions. J. Environ. Prot. vol. 3, pp. 1336-1345, 2012.
- [8] C. Guarnaccia and J. Quartieri, Modeling environmental noise exceedances using non-homogeneous Poisson processes. J. Acoust. Soc. Am. vol. 136, no. 4, pp. 1631–1639, 2014.
- [9] J. Wang, Z. Wu, Y. Shu, and Z. Zhang, An optimized method for software reliability model based on nonhomogeneous Poisson process. Appl. Math. Model. vol. 40, pp. 6324–6339, 2016.
- [10] V. Shinde and J. Kumar, Enhance non-homogeneous Poisson process models incorporating testing effort with coverage function. J. Stat. Manag. Syst. vol. 20, no. 3, pp. 297-308, 2017.
- [11] F. Grabski, Nonhomogenous poisson process application to modeling accidents number at baltic sea waters and ports. Turku, Finland: HAZARD Project, 2017.
- [12] F. Grabski, Nonhomogeneous stochastic processes connected to poisson process. Sci. J. P. Nav. Acad. vol. 2, no. 213, pp. 5-15, 2018.
- [13] B. Fathi-vajargah and H. Khoshkar-foshtomi, Simulating Nonhomogeneous Poisson Point Process Based on Multi-Criteria Intensity Function and Comparison with Its Simple Form. J. Math. Comput. Sci. vol. 9, pp. 133-138, 2014.
- [14] Z. G. Asfaw and B. H. Lindqvist, Unobserved heterogeneity in the power law nonhomogeneous Poisson process. Reliab. Eng. Syst. Saf. vol. 134, pp. 59-65, 2015.
- [15] M. V. Cifuentes-Amado and E. Cepeda-Cuervo, Non-Homogeneous Poisson Process to Model Seasonal Events : Application to the Health Diseases. Int. J. Stat. Med. Res. vol. 4, no. 4, pp. 337-346, 2015.
- [16] V. Slimacek and B. H. Lindqvist, Nonhomogeneous Poisson process with nonparametric frailty. Reliab. Eng. Syst. Saf. vol. 149, pp. 14-23, 2016.
- [17] [N. Leonenko, E. Scalas, and M. Trinh, The fractional non-homogeneous Poisson process. Stat. Probab. Lett. vol. 120, pp. 147-156, 2017.
- [18] A. C. Cebrián, J. Abaurrea, and J. Asín, NHPoisson: An R Package for Fitting and Validating Nonhomogeneous Poisson Processes. J. Stat. Softw. vol. 64, no. 6, 2015.
- [19] N. B. Parwanto and T. Oyama, A statistical analysis and comparison of historical earthquake and tsunami disasters in Japan and Indonesia. Int. J. Disaster Risk Reduct. vol. 7, pp. 122-141, 2014.
- [20] A. Ikram and U. Qamar, Developing an expert system based on association rules and predicate logic for earthquake prediction. Knowledge-Based Syst. vol. 75, pp. 87-103, 2015.
- [21] E. Florido, F. Martínez-Álvarez, A. Morales-Esteban, J. Reyes, and J. L. Aznarte-Mellado, Detecting precursory patterns to enhance earthquake prediction in Chile. Comput. Geosci. vol. 76, pp. 112-120, 2015.
- [22] G. Asencio-Cortés, F. Martínez-Álvarez, A. Morales-Esteban, and J. Reyes, A sensitivity study of seismicity indicators in supervised learning to improve earthquake prediction. Knowledge-Based Syst. vol. 101, pp. 15-30, 2016.
- [23] G. Asencio-Cortés, A. Morales-Esteban, X. Shang, and F. Martínez-Álvarez, “Earthquake prediction in California using regression algorithms and cloud-based big data infrastructure. Comput. Geosci. vol. 115, pp. 198-210, 2018.
- [24] F. Martín-González, Earthquake damage orientation to infer seismic parameters in archaeological sites and historical earthquakes. Tectonophysics, vol. 724-725, pp. 137–145, 2018.
- [25] Y. Xu, T. Ren, Y. Liu, and Z. Li, Earthquake prediction based on community division. Phys. A Stat. Mech. its Appl. vol. 506, pp. 969-974, 2018.
- [26] R. Kurisaki et al., Impact of major earthquakes on Parkinson’s disease. J. Clin. Neurosci. vol. 61, pp. 130-135, 2019.
- [27] R. E. Walpole, R. H. Myers, S. L. Myers, and K. Ye, Probability & Statistics for Engineers & Scientists. Boston: Pearson Education, 2017.
- [28] S. Ross, Introduction to Probability Models. California: Elsevier, 2007.
- [29] N. Nguyen, J. Griffin, A. Cipta, and P. R. Cummins, Indonesia’s Historical Earthquakes: Modelled examples for improving the national hazard map. Canberra: Geoscience Australia, 2015.
- [30] R. B. Darlington and A. F. Hayes, Regression Analysis and Linear Models. New York: Guilford Press, 2013.

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bwmeta1.element.psjd-db8b0e13-b62e-4763-97a0-3c6986a7570a