Abstract

This study provides an overview in combining spatial analysis and time series analysis to model the frequency of earthquake. The aim of this research is to apply the spatial statistical analysis and time series analysis in estimating semivariogram parameters for the next four steps. The data in this study is secondary data that has been validated based on sources that publish parameters of earthquake events. Looking at the characteristics of the earthquake frequency frequency data, there are spatial and time elements. The method used in this research is interpolation kriging and Autoregressive Moving Average (ARMA) model. The semivariogram models used in kriging interpolation are: Spherical, Exponential, Gaussian, and Linear. The parameters of the semivariogram model are modeled using ARMA time series analysis adjusted to the model diagnostic results. To measure of fit model is used Mean Square Error (MSE). The result of research is a suitable semivariogram model to be applied in the modeling of earthquake events is the Spherical model. While each parameter is estimated using ARMA model (2,2) with different coefficient estimation value.

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.