Hawkes processes for Covid-19 patients of estimation Parameters
DOI:
https://doi.org/10.36322/jksc.177(A).19019Keywords:
Hawkes, Self-exciting, Poisson, Counting, Point, Exponential kernel, Conditional intensity, Exponential decayAbstract
The paper dealt with the study of stochastic self-exciting processes called Hawkes processes, where it is usually many accidents as they occurs form data over time, which are called cluster events. That is, the processes of arrival or the occurrence of the event are represented by the cluster samples in which it is the occurrence of each event stimulates the occurrence of another event at an accelerated rate, similar to a cluster. hence it can be said that Hawkes process are a type of stochastic process that can be categorized into many types of data, it is characterized by the fact that its occurrence is followed by the occurrence of accidents rapidly, such as the occurrence of rebounds after a certain earthquake, or any trading operations in finance market or a stock market after a certain jump in trading.
The aim of this paper is to study the behavior of the Hawkes process using a method to estimate the parameters of the Hawkes process, where the quality criterion bias and standard deviation were used to judge the performance of estimation methods in terms of the quality of estimators using patient data Covid-19.
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