Estimating the Parameters of Periodic Bivariate Compound Poisson Process by Inference for Margins Method

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SAKHAEI A.; NASIRI P.

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Journal: JOURNAL OF STATISTICAL SCIENCES Year:2020 | Volume:13 | Issue:2 Page(s): 0-0

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Information Journal Paper

Title

Estimating the Parameters of Periodic Bivariate Compound Poisson Process by Inference for Margins Method

Author(s)

SAKHAEI A. | NASIRI P. | Issue Writer Certificate

Keywords

Non homogeneous Poisson ProcessQ1

Lévy copulaQ1

Short-term periodicQ1

Inference for margins methodQ1

Lévy processQ1

Abstract

The non-homogeneous bivariate compound Poisson process with short term periodic intensity function is used for modeling the events with seasonal patterns or periodic trends. In this paper, this process is carefully introduced. In order to characterize the dependence structure between jumps, the Lé vy copula function is provided. For estimating the parameters of the model, the Inference for margins method is used. As an application, this model is fitted to an automobile insurance dataset with Inference for margins method and its accuracy is compared with the full maximum likelihood method. By using the goodness of fit test, it is confirmed that this model is appropriate for describing the data.

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APA: Copy

SAKHAEI, A., & NASIRI, P.. (2020). Estimating the Parameters of Periodic Bivariate Compound Poisson Process by Inference for Margins Method. JOURNAL OF STATISTICAL SCIENCES, 13(2 ), 0-0. SID. https://sid.ir/paper/370505/en

Vancouver: Copy

SAKHAEI A., NASIRI P.. Estimating the Parameters of Periodic Bivariate Compound Poisson Process by Inference for Margins Method. JOURNAL OF STATISTICAL SCIENCES[Internet]. 2020;13(2 ):0-0. Available from: https://sid.ir/paper/370505/en

IEEE: Copy

A. SAKHAEI, and P. NASIRI, “Estimating the Parameters of Periodic Bivariate Compound Poisson Process by Inference for Margins Method,” JOURNAL OF STATISTICAL SCIENCES, vol. 13, no. 2 , pp. 0–0, 2020, [Online]. Available: https://sid.ir/paper/370505/en

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