Hazard Rate Estimation of Temporal Point Process, Case Study: Earthquake Hazard Rate in Nusatenggara Region
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 33122
Hazard Rate Estimation of Temporal Point Process, Case Study: Earthquake Hazard Rate in Nusatenggara Region

Authors: Sunusi N., Kresna A. J., Islamiyati A., Raupong

Abstract:

Hazard rate estimation is one of the important topics in forecasting earthquake occurrence. Forecasting earthquake occurrence is a part of the statistical seismology where the main subject is the point process. Generally, earthquake hazard rate is estimated based on the point process likelihood equation called the Hazard Rate Likelihood of Point Process (HRLPP). In this research, we have developed estimation method, that is hazard rate single decrement HRSD. This method was adapted from estimation method in actuarial studies. Here, one individual associated with an earthquake with inter event time is exponentially distributed. The information of epicenter and time of earthquake occurrence are used to estimate hazard rate. At the end, a case study of earthquake hazard rate will be given. Furthermore, we compare the hazard rate between HRLPP and HRSD method.

Keywords: Earthquake forecast, Hazard Rate, Likelihood point process, Point process.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1079300

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1498

References:


[1] N.L. Bowers, N.L., H.U. Gerber, J.C. Hickman, and C.J. Nesbitt. Actuarial Mathematics, The Society of Actuaries, 1986. p. 51-59.
[2] D.J. Daley and D. Vere-Jones. An Introduction to the Theory of Point Processes, Springer, Berlin, 2003. p.2-19.
[3] S. Darwis, I.W. Mangku, dan N. Sunusi, Updating Seismic Renewal Model, Far East Journal of Theoretical Statistics, 2008. 27(1), 101- 112.
[4] S. Darwis, S., Sunusi, N., Triyoso, W., dan Mangku, I. W. Single Decrement Approach for Estimating Earthquake Hazard Rate, Advances and Applications in Statistica, 2009. 11(2), 229-237.
[5] R. L. London, FSA, Survival Models and Their Estimation, 3rd Edition, Actex, 1997. p.113-200.
[6] S.G. Ferraes, Probabilistic Prediction of the Next Large Earthquake in the Michoacan Fault-segment of the Mexican Subduction Zone, Geofisica Internacional, 2003. 42, 69-83.
[7] R. Helmers, I.W. Mangku, dan R. Zitikis. Consistent Estimation of the Intensity Function of a Cyclic Poisson Process, Journal of Multivariat Analysis, 2003. 84, 19-39.
[8] R. Helmers, I.W. Mangku,, dan R. Zitikis. Statistical Properties of a Kernel-Type Estimator of the Intensity Function of a Cyclic Poisson Process, Journal of Multivariat Analysis, 2005. 92, 1-23.
[9] Y. Ogata. Seismicity Analysis Through Point Process Modeling: A Review, Pure and Applied Geophysics, 1999.155, 471-507.
[10] T. Rikitake. Probability of an Earthquake Occurrence as Estimated from Crustal Strain, Tectonophysics, 1974. 23, 299-312.
[11] N. Sunusi, S. Darwis, dan W. Triyoso. Estimating Intensity of Point Processes Models Applied to Earthquake Prediction, Mathematics Journal University Teknologi Malaysia, 2008. 2, 405-411.
[12] N. Sunusi, S. Darwis, W. Triyoso, dan I.W. Mangku, Study of Earthquake Forecast through Hazard Rate Analysis, International Journal of Applied Mathematics and Statistics (IJAMAS), 2010. 17(J10), 96-103.
[13] D. Vere-Jones. Forecasting Earthquakes and Earthquakes Risk, International Journal of Forecasting, 11, 1995. 503-538.
[14] V. Yilmaz dan H.E. Celik, A Statistical Approach for Estimating the Probability of Occurrence of Earthquake on the Northern Anatolian Fault Zone, International Journal of Natural and Engineering Science, 2(2), 2008. 81-86.