Kernel Estimation of Rate Function for Recurrent Event Data

DOI10.1111/j.1467-9469.2005.00416.xzbMath1087.62048OpenAlexW2067409885WikidataQ30669740 ScholiaQ30669740MaRDI QIDQ5467686

Chiung-Yu Huang, Mei-Cheng Wang, Chin-Tsang Chiang

Publication date: 24 May 2006

Published in: Scandinavian Journal of Statistics (Search for Journal in Brave)

Full work available at URL: https://biostats.bepress.com/cgi/viewcontent.cgi?article=1027&context=jhubiostat

zbMATH Keywords

bootstrapcensoringPoisson processintensity function

Mathematics Subject Classification ID

Density estimation (62G07) Asymptotic properties of nonparametric inference (62G20) Applications of statistics to biology and medical sciences; meta analysis (62P10) Nonparametric estimation (62G05) Estimation in survival analysis and censored data (62N02)

Related Items (6)

Amplitude and phase variation of point processes ⋮ Semiparametric modelling and estimation of covariate‐adjusted dependence between bivariate recurrent events ⋮ Modeling gap times between recurrent events by marginal rate function ⋮ Semiparametric model for recurrent event data with excess zeros and informative censoring ⋮ On the superposition of overlapping Poisson processes and nonparametric estimation of their intensity function ⋮ Nonparametric estimation and bootstrap confidence intervals for the optimal maintenance time of a repairable system

Cites Work

• Smoothing techniques for curve estimation. Proceedings of a workshop held in Heidelberg, April 2-4, 1979
• The additive nonparametric and semiparametric Aalen model as the rate function for a counting process
• Semiparametric Regression for the Mean and Rate Functions of Recurrent Events

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