In this paper we discuss semiparametric additive isotonic regression models. We discuss the efficiency bound of the model and the least squares estimator under this model. We show that the ordinary least square estimator studied by Huang (2002) and Cheng (2009) for the semiparametric isotonic regression achieves the efficiency bound for the regular estimator when the true parameter belongs to the interior of the parameter space. We also show that the result by Cheng (2009) can be generalized to the case that the covariates are dependent on each other. (C) 2013 The Korean Statistical Society. Published by Elsevier B.V. All rights reserved.
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Univ Washington, Dept Stat, Box 354322, Seattle, WA 98195 USAUniv Washington, Dept Stat, Box 354322, Seattle, WA 98195 USA
Han, Qiyang
Wang, Tengyao
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Univ Cambridge, Cambridge, England
Stat Lab, Wilberforce Rd, Cambridge CB3 0WB, EnglandUniv Washington, Dept Stat, Box 354322, Seattle, WA 98195 USA
Wang, Tengyao
Chatterjee, Sabyasachi
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Univ Chicago, Chicago, IL 60637 USA
Univ Illinois, Dept Staist, Illini Hall,Room 117,725 S Wright St, Champaign, IL 61820 USAUniv Washington, Dept Stat, Box 354322, Seattle, WA 98195 USA
Chatterjee, Sabyasachi
Samworth, Richard J.
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Univ Cambridge, Cambridge, England
Stat Lab, Wilberforce Rd, Cambridge CB3 0WB, EnglandUniv Washington, Dept Stat, Box 354322, Seattle, WA 98195 USA
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Stanford Univ, Dept Stat, Stanford, CA 94305 USAStanford Univ, Dept Stat, Stanford, CA 94305 USA
Tibshirani, Ryan J.
Hoefling, Holger
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Novartis, Mol Diagnost, CH-4002 Basel, SwitzerlandStanford Univ, Dept Stat, Stanford, CA 94305 USA
Hoefling, Holger
Tibshirani, Robert
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Stanford Univ, Dept Hlth, Stanford, CA 94305 USA
Stanford Univ, Dept Res & Policy, Stanford, CA 94305 USA
Stanford Univ, Dept Stat, Stanford, CA 94305 USAStanford Univ, Dept Stat, Stanford, CA 94305 USA