Statistical inference on transformation models: a self-induced smoothing approach

DOI10.1080/10485252.2018.1424334zbMath1404.62043arXiv1302.6651OpenAlexW2964013558MaRDI QIDQ4643624

Yongzhao Shao, Junyi Zhang, Zhezhen Jin, Zhiliang Ying

Publication date: 28 May 2018

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

Full work available at URL: https://arxiv.org/abs/1302.6651

zbMATH Keywords

asymptotic normalitysemiparametric modelsvariance estimationrank correlationHoeffding's decompositionU-processcensored regression modelalgorithmic convergenceextreme value densityself-induced smoothing

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Nonparametric regression and quantile regression (62G08) Density estimation (62G07) Applications of statistics to biology and medical sciences; meta analysis (62P10) Censored data models (62N01) Statistics of extreme values; tail inference (62G32)

Related Items (2)

The ROC of Cox proportional hazards cure models with application in cancer studies ⋮ Maximum pairwise-rank-likelihood-based inference for the semiparametric transformation model

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