Adaptive Lasso Variable Selection for the Accelerated Failure Models
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Publication:2892638
DOI10.1080/03610926.2010.513785zbMath1239.62129OpenAlexW2080480825MaRDI QIDQ2892638
Publication date: 19 June 2012
Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/03610926.2010.513785
Asymptotic properties of parametric estimators (62F12) Ridge regression; shrinkage estimators (Lasso) (62J07) Censored data models (62N01) Estimation in survival analysis and censored data (62N02) Reliability and life testing (62N05)
Related Items (7)
Bayesian penalized Buckley-James method for high dimensional bivariate censored regression models ⋮ Bayesian analysis of penalized quantile regression for longitudinal data ⋮ Shrinkage estimation in lognormal regression model for censored data ⋮ Adaptive group bridge selection in the semiparametric accelerated failure time model ⋮ A fast algorithm for the accelerated failure time model with high-dimensional time-to-event data ⋮ Covariate selection for accelerated failure time data ⋮ Perturbation bootstrap in adaptive Lasso
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