Nonparametric estimation of intensities of nonhomogeneous Poisson processes

DOI10.1007/BF02925534zbMath0769.62031OpenAlexW2046490461MaRDI QIDQ4695026

Hendrik Schäbe

Publication date: 18 July 1993

Published in: Statistical Papers (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/bf02925534

zbMATH Keywords

consistencylimiting distributionalmost sure convergencekernel estimatornonhomogeneous Poisson processintensity estimationcross validation proceduredata driven bandwidthL2-procedures

Mathematics Subject Classification ID

Density estimation (62G07) Asymptotic distribution theory in statistics (62E20) Asymptotic properties of nonparametric inference (62G20) Central limit and other weak theorems (60F05) Markov processes: estimation; hidden Markov models (62M05)

Cites Work

• Unnamed Item
• Smoothing counting process intensities by means of kernel functions
• Statistical analysis of counting processes
• On the amount of noise inherent in bandwidth selection for a kernel density estimator
• Nonparametric inference for a family of counting processes
• Biased and Unbiased Cross-Validation in Density Estimation
• Hedging and Maxmin
• Martingales on Jump Processes. I: Representation Results
• Martingales on Jump Processes. II: Applications

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