Modeling Non-Homogenous Poisson Process and Estimating the Intensity Function for Earthquake Occurrences in Iraq using Simulation for data from January 1st 2018 to April 30th 2023.

The Non-homogeneous Poisson Process, with time-dependent intensity functions, is commonly used to model the scenario of counting the number of events that appear to occur in a given time interval. The identification of the process relies on the functional form of the intensity function, which can be difficult to determine. In this paper, a Non-Homogenous Poisson Process model is proposed to predict the intensity function for the number of earthquake occurrences in Iraq; the constructed model allows anticipating the number of earthquakes that occur at any time interval with a specific time length. Then, to estimate the model parameters, the data obtained from the annual reports of the Iraqi Meteorological Organization and Seismology (IMOS) from January 1st 2018 to April 30th 2023 are used. Moreover, a simulation study is conducted and a new algorithm is introduced to show the performance and applicability of the proposed model. [ABSTRACT FROM AUTHOR]