A rate of consistency for nonparametric estimators of the distribution function based on censored dependent data

DOI10.1007/s10260-018-00445-7zbMath1427.62021OpenAlexW2901676272MaRDI QIDQ2324304

Nahima Nemouchi, Fatiha Messaci, Nour El Houda Rouabah

Publication date: 11 September 2019

Published in: Statistical Methods and Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10260-018-00445-7

zbMATH Keywords

rate of convergencecensoring\(\alpha \)-mixingalmost complete convergenceproduct-limit estimators

Mathematics Subject Classification ID

Asymptotic properties of nonparametric inference (62G20) Applications of statistics to environmental and related topics (62P12) Nonparametric estimation (62G05) Censored data models (62N01)

Related Items (1)

Unnamed Item

Uses Software

• NADA

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Uniform strong estimation under \(\alpha\)-mixing, with rates
• Mixing: Properties and examples
• The Kaplan-Meier estimate for dependent failure time observations
• Rate of strong consistency for nonparametric estimators based on twice censored data
• Product-limit estimators of the survival function with twice censored data
• Nonparametric functional data analysis. Theory and practice.
• A survey of product-integration with a view toward application in survival analysis
• Nonparametric Estimation from Incomplete Observations
• Conditions for linear processes to be strong-mixing
• On the Strong Mixing Property for Linear Sequences
• Estimating a distribution function for censored time series data

This page was built for publication: A rate of consistency for nonparametric estimators of the distribution function based on censored dependent data