Penerapan Sebaran Generalized Extreme Value (Gev) untuk Menduga Kejadian Ekstrim

Achi Rinaldi


The Generalized Extreme Value (GEV) is a distribution that can describe extreme values. Modeling for extreme values is very useful in estimating extreme events, such as extreme rainfall that can cause flooding. This study aims to make extreme rainfall models through the spatial effect that succeed in forming special zones. In addition,  it is also studied on time series patterns that can be explained through extremogram. The effect of spatial and time series are then modeled spatiotemporally by the Bayes hierarchy method through the concept of Integrated Laplace Approximation (INLA). The application of models for extreme values with GEV is expected to be a reference for policymakers, especially in the context of disaster mitigation due to extreme events.


Hierarchical Bayes, GEV, extreme event, INLA, spatio-temporal

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Blangiardo, M. and Cameletti, M., 2015. Spatial and spatio-temporal Bayesian models with R-INLA. John Wiley & Sons.

Cooley, D., Naveau, P. and Poncet, P., 2006. Variograms for spatial max-stable random fields. In Dependence in probability and statistics (pp. 373-390). Springer, New York, NY.

Cooley D, Nychka D, and Naveau P., 2007. Bayes spatial modeling of extreme precipitation return levels. Journal of the American Statistical Association, 102: 824-840.

Davis, R.A. and Mikosch, T., 2009. The extremogram: A correlogram for extreme events. Bernoulli, 15(4), pp.977-1009.

Davison, A.C., Padoan, S.A. and Ribatet, M., 2012. Statistical modeling of spatial extremes. Statistical science, 27(2), pp.161-186.

Rinaldi, A., 2015. Aplikasi Model Persamaan Struktural Pada Program R (Studi Kasus Data Pengukuran Kecerdasan). Al-Jabar: Jurnal Pendidikan Matematika, 6(1), pp.1-12.

Rinaldi, A., 2016. Sebaran Generalized Extreme Value (GEV) dan Generalized Pareto (GP) untuk Pendugaan Curah Hujan Ekstrim di Wilayah DKI Jakarta. Al-Jabar: Jurnal Pendidikan Matematika, 7(1), pp.75-84.

Rinaldi, A., Djuraidah, A., Wigena, A.H., Mangku, I.W. and Gunawan, D., 2017. Spatial extreme models with copula to determine extreme rainfall zone. Applied Mathematical Sciences, 11(27), pp.1327-1336.

Rinaldi, A., 2018. Pengembangan Model Spatio-temporal Conditional Autoregressive untuk Pendugaan Curah Hujan Ekstrim di Wilayah Jawa Barat. [Disertasi]. Bogor: Program Pascasarjana, Institut Pertanian Bogor.

Rinaldi, A., Djuraidah, A., Wigena, A.H., Mangku, I.W. and Gunawan, D., 2018. Identification of Extreme Rainfall Pattern Using Extremogram in West Java. In IOP Conference Series: Earth and Environmental Science (Vol. 187, No. 1, p. 012064). IOP Publishing.

Rue, H. and Held, L., 2005. Gaussian Markov random fields: theory and applications. Chapman and Hall/CRC.

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