Penalized maximum likelihood estimation for a function of the intensity of a Poisson point process

被引:0
|
作者
Dias R. [1 ]
Ferreira C.S. [1 ]
Garcia N.L. [1 ]
机构
[1] Departamento de Estatística, IMECC, UNICAMP, 13.081-970 Campinas, SP
基金
巴西圣保罗研究基金会;
关键词
H-splines; Nonparametric estimation; Poisson processes;
D O I
10.1007/s11203-006-9005-5
中图分类号
学科分类号
摘要
Let f: [a,b] → ℝ be an unknown 2 times differentiable function and consider M to be an α- homogeneous Poisson process on Graf(f). The goal is to estimate f having a sample of the inhomogeneous Poisson process N constructed by dislocating each point of M perpendicularly to Graf(f) by a normal random variable with zero mean and constant variance σ2. The exact formulas for the mean measure and the intensity function of N are obtained. Then, the function f is estimated directly using a hybrid spline approach to penalized maximum likelihood. Simulation results indicate the procedure to be consistent as α → ∞ and σ2 → 0. © 2006 Springer Science+Business Media, LLC.
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页码:11 / 34
页数:23
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