Variable selection in a partially linear proportional hazards model with a diverging dimensionality

DOI10.1016/j.spl.2012.08.024zbMath1489.62307OpenAlexW2026035519MaRDI QIDQ1933699

Yuao Hu, Heng Lian

Publication date: 25 January 2013

Published in: Statistics \& Probability Letters (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.spl.2012.08.024

zbMATH Keywords

partial likelihoodcross-validationBayesian information criterion (BIC)SCADAkaike information criterion (AIC)

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Ridge regression; shrinkage estimators (Lasso) (62J07) Nonparametric estimation (62G05) Estimation in survival analysis and censored data (62N02)

Related Items (8)

SCAD-penalized regression in additive partially linear proportional hazards models with an ultra-high-dimensional linear part ⋮ Feature screening in ultrahigh-dimensional varying-coefficient Cox model ⋮ Variable selection in Cox regression models with varying coefficients ⋮ Robust estimation and variable selection in censored partially linear additive models ⋮ Variable selection in partially linear additive hazards model with grouped covariates and a diverging number of parameters ⋮ Partial linear modelling with multi-functional covariates ⋮ Sparse nonparametric model for regression with functional covariate ⋮ Penalised empirical likelihood for the additive hazards model with high-dimensional data

Uses Software

• hgam

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