Nonparametric estimation of the cumulative intensity function for a nonhomogeneous Poisson process from overlapping realizations

• 成果类型: Article
• 署名作者: Arkin, BL; Leemis, LM
• 署名单位: William & Mary
• 刊物名称: MANAGEMENT SCIENCE
• ISSN/ISSBN: 0025-1909
• DOI: 10.1287/mnsc.46.7.989.12037
• 发表日期: 2000
• 页码: 989-998
• 关键词: input modeling; nonstationary Poisson process; repairable systems; simulation; time-dependent arrivals; variate generation

摘要

A nonparametric technique for estimating the cumulative intensity function of a nonhomogeneous Poisson process from one or more realizations on an interval is extended here to include realizations that overlap. This technique does not require any arbitrary parameters from the modeler, and the estimated cumulative intensity function can be used to generate a point process for simulation by inversion.