Analysis of Data from a Series of Events by a Geometric Process Model |
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Authors: | Email author" target="_blank">Yeh?LamEmail author Li-xing?Zhu Jennifer?S?K?Chan Qun?Liu |
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Institution: | (1) Northeastern University at Qinhuangdao, 066004 Qinhuangdao, China;(2) Department of Statistics and Actuarial Science, The University of Hong Kong, Hong Kong, Hong Kong;(3) Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, China |
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Abstract: | Geometric process was first introduced by Lam.A stochastic process {X_i,i=1,2,...} iscalled a geometric process (GP) if,for some a>0,{a~(i-1)X_i,i=1,2,...} forms a renewal process.In thispaper,the GP is used to analyze the data from a series of events.A nonparametric method is introduced forthe estimation of the three parameters in the GP.The limiting distributions of the three estimators are studied.Through the analysis of some real data sets,the GP model is compared with other three homogeneous andnonhomogeneous Poisson models.It seems that on average the GP model is the best model among these fourmodels in analyzing the data from a series of events. |
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Keywords: | Nonhomogeneous poisson process hazard function renewal process geometric process limiting distribution the lindeberg-feller theorem |
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