High-dimensional additive hazards models and the lasso

DOI10.1214/12-EJS681zbMath1274.62655arXiv1106.4662OpenAlexW2014738419WikidataQ98839738 ScholiaQ98839738MaRDI QIDQ1950827

Agathe Guilloux, Stéphane Gaïffas

Publication date: 28 May 2013

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

Full work available at URL: https://arxiv.org/abs/1106.4662

zbMATH Keywords

survival analysiscensored datacounting processesLassohigh-dimensional covariatesAalen additive modeldata-driven Bernstein's inequality

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Estimation in survival analysis and censored data (62N02)

Related Items (14)

Oracle inequalities for the Lasso in the high-dimensional Aalen multiplicative intensity model ⋮ Concentration inequalities, counting processes and adaptive statistics ⋮ Limit theorems and inequalities via martingale methods ⋮ Oracle inequalities for the lasso in the Cox model ⋮ Tests for Coefficients in High-dimensional Additive Hazard Models ⋮ ESTIMATION OF A HIGH-DIMENSIONAL COUNTING PROCESS WITHOUT PENALTY FOR HIGH-FREQUENCY EVENTS ⋮ Treatment Effect Estimation Under Additive Hazards Models With High-Dimensional Confounding ⋮ ESTIMATION FOR THE PREDICTION OF POINT PROCESSES WITH MANY COVARIATES ⋮ Concentration inequalities for matrix martingales in continuous time ⋮ Oracle inequalities for the Lasso in the additive hazards model with interval-censored data ⋮ Inference under Fine-Gray competing risks model with high-dimensional covariates ⋮ Sparse space-time models: concentration inequalities and Lasso ⋮ Structured estimation for the nonparametric Cox model ⋮ Lasso and probabilistic inequalities for multivariate point processes

Uses Software

• timereg

Cites Work

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• The Adaptive Lasso and Its Oracle Properties
• Penalized projection estimators of the Aalen multiplicative intensity
• The Dantzig selector and sparsity oracle inequalities
• Adaptive Dantzig density estimation
• Nuclear-norm penalization and optimal rates for noisy low-rank matrix completion
• Sparsity in penalized empirical risk minimization
• The additive hazards model with high-dimensional regressors
• SPADES and mixture models
• Variable selection for Cox's proportional hazards model and frailty model
• Least angle regression. (With discussion)
• Exponential inequalities for martingales, with application to maximum likelihood estimation for counting processes
• Adaptive estimation of the conditional intensity of marker-dependent counting processes
• On the conditions used to prove oracle results for the Lasso
• Lasso and probabilistic inequalities for multivariate point processes
• Simultaneous analysis of Lasso and Dantzig selector
• Aggregation for Gaussian regression
• Additive risk model with case-cohort sampled current status data
• The Dantzig selector: statistical estimation when \(p\) is much larger than \(n\). (With discussions and rejoinder).
• Dynamic regression models for survival data.
• Covariate Selection for the Semiparametric Additive Risk Model
• The Dantzig Selector in Cox's Proportional Hazards Model
• A note on path-based variable selection in the penalized proportional hazards model
• Semiparametric analysis of the additive risk model
• A partly parametric additive risk model
• A Framework for Feature Selection in Clustering
• Adaptive Lasso for Cox's proportional hazards model
• Additive Risk Models for Survival Data with High‐Dimensional Covariates
• Statistical models based on counting processes

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