Nonparametric kernel regression when the regressor follows a counting process

DOI10.1080/10485259608832680zbMath0879.62036OpenAlexW2065433911MaRDI QIDQ4345903

Thomas H. Scheike

Publication date: 16 December 1997

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

Full work available at URL: https://doi.org/10.1080/10485259608832680

zbMATH Keywords

kernel estimationcensoringnonparametric regressionAalen's multiplicative model

Mathematics Subject Classification ID

Density estimation (62G07) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Asymptotic properties of nonparametric inference (62G20)

Related Items (1)

Cumulative regression function tests for regression models for longitudinal data

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Smoothing splines: Regression, derivatives and deconvolution
• Smoothing counting process intensities by means of kernel functions
• Additive regression and other nonparametric models
• Nonparametric inference for a family of counting processes
• Local linear regression smoothers and their minimax efficiencies
• Smoothing by spline functions.
• On empirical spectral analysis of stochastic processes
• Central limit theorems for local martingales
• Martingales on Jump Processes. I: Representation Results
• On Non-Parametric Estimates of Density Functions and Regression Curves

This page was built for publication: Nonparametric kernel regression when the regressor follows a counting process