Statistical inference for conditional curves: Poisson process approach

DOI10.1214/aos/1176348656zbMath0760.62035OpenAlexW1966813842MaRDI QIDQ1193350

Rolf-Dieter Reiss, Michael Falk

Publication date: 27 September 1992

Published in: The Annals of Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1214/aos/1176348656

zbMATH Keywords

asymptotic normalityHellinger distanceregression quantilesnonparametric regressionprojection pursuitconditional distributionapproximation errorconditional quantilesunified treatmentfunctional parameterconditional \(V\)-statisticsconditional curvesestimation of regression meansPoisson approximation of truncated, empirical point processesregression functionals

Mathematics Subject Classification ID

Density estimation (62G07) Asymptotic properties of nonparametric inference (62G20) Linear inference, regression (62J99) Point processes (e.g., Poisson, Cox, Hawkes processes) (60G55)

Related Items (3)

Efficient estimation in local parametric regression analysis ⋮ Residual life functionals at great age ⋮ The local bootstrap for Markov processes

This page was built for publication: Statistical inference for conditional curves: Poisson process approach