A boosting first-hitting-time model for survival analysis in high-dimensional settings

DOI10.1007/s10985-022-09553-9OpenAlexW4225001829MaRDI QIDQ6103255

Riccardo De Bin, Vegard Grødem Stikbakke

Publication date: 26 June 2023

Published in: Lifetime Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10985-022-09553-9

zbMATH Keywords

Wiener processphase-type distributionCox modeldata integrationfirst hitting timegradient boostingtime-to-event outcome

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Survival analysis and censored data (62Nxx)

Related Items

Semiparametric predictive inference for failure data using first-hitting-time threshold regression

Cites Work

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• Model-based boosting in R: a hands-on tutorial using the R package mboost
• Boosting algorithms: regularization, prediction and model fitting
• On the choice and influence of the number of boosting steps for high-dimensional linear Cox-models
• Boosting in Cox regression: a comparison between the likelihood-based and the model-based approaches with focus on the R-packages \textit{CoxBoost} and \textit{mboost}
• Proportional hazards and threshold regression: their theoretical and practical connections
• The additive hazards model with high-dimensional regressors
• Survival and event history analysis. A process point of view
• A review of the methods for signal estimation in stochastic diffusion leaky integrate-and-fire neuronal models
• Understanding the shape of the hazard rate: A process point of view. (With comments and a rejoinder).
• An update on statistical boosting in biomedicine
• Gradient boosting for distributional regression: faster tuning and improved variable selection via noncyclical updates
• Survival models based on the Ornstein-Uhlenbeck process
• Additive logistic regression: a statistical view of boosting. (With discussion and a rejoinder by the authors)
• Boosting a weak learning algorithm by majority
• Estimating degradation by a Wiener diffusion process subject to measurement error
• Phase-type distributions in population genetics
• A gradient boosting algorithm for survival analysis via direct optimization of concordance index
• Threshold regression for survival analysis: modeling event times by a stochastic process reaching a boundary
• Matrix-Exponential Distributions in Applied Probability
• Boosting With theL₂Loss
• Beyond mean regression
• Survival Regression with Accelerated Failure Time Model in XGBoost
• Generalized Additive Models for Location, Scale and Shape