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  • Search: subject:"Distorting function"
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Year of publication
Subject
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Distorting function 3 Single index 2 Coordinate-independent sparse estimation (CISE) 1 Correlation coefficient 1 Covariate adjusted 1 Covariate-adjusted regression 1 Dimension reduction 1 Empirical likelihood 1 Error-prone 1 Estimating equation function 1 Kernel smoothing 1 Local linear smoothing 1 Measurement error models 1 Measurement errors 1 Measurement errors models 1 Minimum average variance estimation (MAVE) 1 Sparse principle component (SPC) 1
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Undetermined 3
Type of publication
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Article 3
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Undetermined 3
Author
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Zhang, Jun 3 Liang, Hua 2 Zhu, Li-Xing 2 Feng, Zhenghui 1 Yu, Yao 1 Zhou, Bu 1
Published in...
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Journal of Multivariate Analysis 2 Annals of the Institute of Statistical Mathematics 1
Source
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RePEc 3
Showing 1 - 3 of 3
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A revisit to correlation analysis for distortion measurement error data
Zhang, Jun; Feng, Zhenghui; Zhou, Bu - In: Journal of Multivariate Analysis 124 (2014) C, pp. 116-129
In this paper, we consider the estimation problem of a correlation coefficient between unobserved variables of interest. These unobservable variables are distorted in a multiplicative fashion by an observed confounding variable. Two estimators, the moment-based estimator and the direct plug-in...
Persistent link: https://www.econbiz.de/10010737770
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Partial linear single index models with distortion measurement errors
Zhang, Jun; Yu, Yao; Zhu, Li-Xing; Liang, Hua - In: Annals of the Institute of Statistical Mathematics 65 (2013) 2, pp. 237-267
We study partial linear single index models when the response and the covariates in the parametric part are measured with errors and distorted by unknown functions of commonly observable confounding variables, and propose a semiparametric covariate-adjusted estimation procedure. We apply the...
Persistent link: https://www.econbiz.de/10010634435
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Nonlinear models with measurement errors subject to single-indexed distortion
Zhang, Jun; Zhu, Li-Xing; Liang, Hua - In: Journal of Multivariate Analysis 112 (2012) C, pp. 1-23
We study nonlinear regression models whose both response and predictors are measured with errors and distorted as single-index models of some observable confounding variables, and propose a multicovariate-adjusted procedure. We first examine the relationship between the observed primary...
Persistent link: https://www.econbiz.de/10010594241
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