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Semiparametric Analysis of Isotonic Errors-in-Variables Regression Models with Missing Response
Ist Teil von
Communications in statistics. Theory and methods, 2012-06, Vol.41 (11), p.2034-2060
Ort / Verlag
Philadelphia, PA: Taylor & Francis Group
Erscheinungsjahr
2012
Link zum Volltext
Quelle
Taylor & Francis Journals Auto-Holdings Collection
Beschreibungen/Notizen
This article is concerned with the estimation problem in the semiparametric isotonic regression model when the covariates are measured with additive errors and the response is missing at random. An inverse marginal probability weighted imputation approach is developed to estimate the regression parameters and a least-square approach under monotone constraint is employed to estimate the functional component. We show that the proposed estimator of the regression parameter is root-n consistent and asymptotically normal and the isotonic estimator of the functional component, at a fixed point, is cubic root-n consistent. A simulation study is conducted to examine the finite-sample properties of the proposed estimators. A data set is used to demonstrate the proposed approach.