Statistical properties of a kernel-type estimator of the intensity function of a cyclic Poisson process

DOI10.1016/S0047-259X(03)00082-4zbMath1075.62025OpenAlexW1968227404MaRDI QIDQ2486169

Ričardas Zitikis, Roelof Helmers, I. Wayan Mangku

Publication date: 5 August 2005

Published in: Journal of Multivariate Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/s0047-259x(03)00082-4

zbMATH Keywords

Poisson processVarianceNonparametric estimationConsistencyBiasPeriodIntensity functionMean-squared errorPoint process

Mathematics Subject Classification ID

Density estimation (62G07) Asymptotic properties of nonparametric inference (62G20) Non-Markovian processes: estimation (62M09) Markov processes: estimation; hidden Markov models (62M05) Inference from stochastic processes (62M99) Point processes (e.g., Poisson, Cox, Hawkes processes) (60G55)

Related Items (7)

Estimating the intensity of a cyclic Poisson process in the presence of linear trend ⋮ Predicting a cyclic Poisson process ⋮ Confidence regions for the intensity function of a cyclic Poisson process ⋮ Estimation of the intensity of non-homogeneous point processes via wavelets ⋮ Estimating the Period of a Cyclic Non‐Homogeneous Poisson Process ⋮ A non-parametric estimator for the doubly periodic Poisson intensity function ⋮ Adaptive policies for perimeter surveillance problems

Cites Work

• An introduction to the theory of point processes
• Statistical inference for spatial Poisson processes
• On estimation of Poisson intensity functions
• Consistent estimation of the intensity function of a cyclic Poisson process.
• A course on point processes
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