Nonparametric estimation in [alpha]-series processes

Halil Aydogdu and Mahmut Kara

Computational Statistics & Data Analysis, 2012, vol. 56, issue 1, 190-201

Abstract: A counting process with the interoccurrence times X1,X2,... is an [alpha]-series process if there exists a real number [alpha] such that (k[alpha]Xk)k=1,2,... forms a renewal process. The nonparametric inference problem in an [alpha]-series process is taken into consideration. The Mann test is applied for trend analysis and a graphical technique is presented in order to test whether the data come from an [alpha]-series process. Some nonparametric estimators for three important parameters of the [alpha]-series process are obtained by using a linear regression method. The consistency and asymptotic normality properties are investigated. The performances of the estimators are evaluated by a simulation study. Some suggestions on the choice of the estimators are made based on the theoretical and simulation results. Further, the method is illustrated through a real-life example.

Keywords: [alpha]-series; process; Trend; Linear; regression (search for similar items in EconPapers)
Date: 2012
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:csdana:v:56:y:2012:i:1:p:190-201

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