A presmoothing approach for estimation in the semiparametric Cox mixture cure model

DOI10.3150/21-BEJ1434OpenAlexW4293490344MaRDI QIDQ2676938

Eni Musta, Valentin Patilea, Ingrid Van Keilegom

Publication date: 28 September 2022

Published in: Bernoulli (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2008.05338

zbMATH Keywords

kernel smoothingsurvival analysislogistic modelcure models

Mathematics Subject Classification ID

Survival analysis and censored data (62Nxx) Applications of statistics (62Pxx) Nonparametric inference (62Gxx)

Uses Software

• Smcure

Cites Work

• Unnamed Item
• Cox's regression model for counting processes: A large sample study
• Maximum likelihood estimation in the proportional hazards cure model
• A class of linear regression parameter estimators constructed by nonparametric estimation
• Transfer of tail information in censored regression models
• Uniform strong representation of the conditional Kaplan-Meier process
• Weak convergence and empirical processes. With applications to statistics
• A general approach for cure models in survival analysis
• A likelihood-based approach for cure regression models
• Presmoothing in functional linear regression
• Semi-Parametric Estimation in Failure Time Mixture Models
• Estimation in a Cox Proportional Hazards Cure Model
• A Nonparametric Mixture Model for Cure Rate Estimation
• Model selection in regression based on pre-smoothing
• The single‐index/Cox mixture cure model
• Mixture Cure Models in Prediction of Time to Default: Comparison with Logit and Cox Models
• Nonparametric cure rate estimation with covariates
• Estimation of Semiparametric Models when the Criterion Function Is Not Smooth
• Goodness-of-fit tests for the cure rate in a mixture cure model
• A mixture model combining logistic regression with proportional hazards regression

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