Semiparametric additive transformation model under current status data

DOI10.1214/11-EJS656zbMath1329.62197arXiv1105.1304OpenAlexW1981276144MaRDI QIDQ1952246

Xiao Wang, Guang Cheng

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/1105.1304

zbMATH Keywords

efficient estimationB-splinecurrent status datasemiparametric transformation modelsconsistent variance estimation

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Nonparametric regression and quantile regression (62G08) Asymptotic properties of nonparametric inference (62G20) Censored data models (62N01)

Related Items (12)

Efficient nonparametric estimation of distribution for current status censoring ⋮ Regression analysis of current status data with auxiliary covariates and informative observation times ⋮ Efficient estimation of semiparametric copula models for bivariate survival data ⋮ Adaptive estimation of the conditional cumulative distribution function from current status data ⋮ Efficient estimation of the varying-coefficient partially linear proportional odds model with current status data ⋮ Efficient estimation of a varying-coefficient partially linear proportional hazards model with current status data ⋮ Variable selection for nonparametric additive Cox model with interval‐censored data ⋮ Estimation of partly linear additive hazards model with left-truncated and right-censored data ⋮ Variable selection in partially linear additive hazards model with grouped covariates and a diverging number of parameters ⋮ Estimation of partially linear single-index additive hazards model with current status data ⋮ A penalized likelihood approach for efficiently estimating a partially linear additive transformation model with current status data ⋮ Kernel machines for current status data

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