Nonparametric estimation of the bivariate survival function for one modified form of current-status data

DOI10.1080/00949655.2010.480944zbMath1431.62444OpenAlexW1965956003MaRDI QIDQ4914968

Pao-sheng Shen, Jai-Chi Kang

Publication date: 16 April 2013

Published in: Journal of Statistical Computation and Simulation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00949655.2010.480944

zbMATH Keywords

bivariate distributionright-censoringleft-censoring

Mathematics Subject Classification ID

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)

Cites Work

• Unnamed Item
• Product-limit estimators of the survival function for two modified forms of current-status data
• Kaplan-Meier estimate on the plane
• Kaplan-Meier estimate on the plane: Weak convergence, LIL, and the bootstrap
• Efficient estimation in the bivariate censoring model and repairing NPMLE
• Weak convergence and empirical processes. With applications to statistics
• Bivariate current status data with univariate monitoring times
• Covariance and survivor function estimation using censored multivariate failure time data
• Nonparametric estimators of the bivariate survival function under random censoring
• Asymptotic normality of the NPMLE of linear functionals for interval censored data, case 1
• Small sample comparison of six bivariate survival curve estimators¹
• On Weak Convergence of Stochastic Processes with Multidimensional Time Parameter

This page was built for publication: Nonparametric estimation of the bivariate survival function for one modified form of current-status data