Results 201 to 210 of about 2,902,778 (234)
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Root-N-Consistent Semiparametric Regression
Econometrica, 1988Summary: One type of semiparametric regression on an \({\mathcal R}\) \(p\times {\mathcal R}\) q-valued random variable (X,Z) is \(\beta 'X+\theta (Z)\), where \(\beta\) and \(\theta\) (Z) are an unknown slope coefficient vector and function, and X is neither wholly dependent on Z nor necessarily independent of it.
P. Robinson
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On semiparametric regression in functional data analysis
WIREs Computational Statistics, 2020The aim of this paper is to provide a selected advanced review on semiparametric regression which is an emergent promising field of researches in functional data analysis.
N. Ling, P. Vieu
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Semiparametric model averaging prediction for lifetime data via hazards regression
Journal of the Royal Statistical Society: Series C (Applied Statistics), 2021Forecasting survival risks for time‐to‐event data is an essential task in clinical research. Practitioners often rely on well‐structured statistical models to make predictions for patient survival outcomes.
Jialiang Li +3 more
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SEMIPARAMETRIC TIME SERIES REGRESSION
Journal of Time Series Analysis, 1994Abstract.Let (Xi,Yi),i= 0, pL 1,… denote a bivariate stationary time series withXibeing Rd‐valued andYibeing real‐valued. We consider the regression modelYi=θ(Xi) +Zi, where θ(·) is an unknown function and Ziis an autoregressive process. Given a realization of lengthn, we examine the problem of estimating the nonparametric function θ(·) and the ...
Truong, Young K., Stone, Charles J.
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IEEE transactions on fuzzy systems, 2019
In the multivariate linear regression model, it is desirable to include the important explanatory variables to achieve maximal prediction. In this context, the present paper is an attempt to extend the conventional elastic net multiple linear regression ...
M. Akbari, G. Hesamian
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In the multivariate linear regression model, it is desirable to include the important explanatory variables to achieve maximal prediction. In this context, the present paper is an attempt to extend the conventional elastic net multiple linear regression ...
M. Akbari, G. Hesamian
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Semiparametric regression model selections
Journal of Statistical Planning and Inference, 1999zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Shi, Peide, Tsai, Chih-Ling
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Semiparametric Regression Functionals
Journal of the American Statistical Association, 1995Abstract A regression method is developed for a general class of functionals. A semiparametric linear model is adopted, and the regression parameters are estimated by maximizing a profiled nonparametric or empirical likelihood based on a local estimate of the conditional distribution function.
Michael Leblanc, John Crowley
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Efficiency Bounds for Semiparametric Regression
Econometrica, 1992zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Semiparametric regression control charts
Journal of Statistical Theory and Practice, 2016zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Chen, Yuhui, Hanson, Timothy
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Semiparametric partially linear varying coefficient modal regression
Journal of Econometrics, 2022A. Ullah, Tao Wang, W. Yao
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