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Statistical inference for partially linear errors-in-variables panel data models with fixed effects
Systems Science & Control Engineering, 2021 In this paper, we consider the statistical inference for the partially linear panel data models with fixed effects. We focus on the case where some covariates are measured with additive errors. We propose a modified profile least squares estimator of the
Bangqiang He, Minxiu Yu, Jinming Zhou
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Prediction in polynomial errors-in-variables models
Modern Stochastics: Theory and Applications, 2020 A multivariate errors-in-variables (EIV) model with an intercept term, and a polynomial EIV model are considered. Focus is made on a structural homoskedastic case, where vectors of covariates are i.i.d. and measurement errors are i.i.d. as well.
Alexander Kukush, Ivan Senko
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Minimax Rates of ℓp-Losses for High-Dimensional Linear Errors-in-Variables Models over ℓq-Balls
Entropy, 2021 In this paper, the high-dimensional linear regression model is considered, where the covariates are measured with additive noise. Different from most of the other methods, which are based on the assumption that the true covariates are fully obtained ...
Xin Li, Dongya Wu
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Estimation in a linear errors-in-variables model under a mixture of classical and Berkson errors
Modern Stochastics: Theory and Applications, 2021 A linear structural regression model is studied, where the covariate is observed with a mixture of the classical and Berkson measurement errors. Both variances of the classical and Berkson errors are assumed known.
Mykyta Yakovliev, Alexander Kukush
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Testing straightness of line objects using total least squares [PDF]
Tehnika, 2017 The paper presents the adaptation (fitting) of a set of points, with an estimated two-dimensional positions, to the straight line model of the by the application of the Weighted Total Least Squares, WTLS.
Popović Jovan +4 more
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Two models for linear comparative calibration [PDF]
International Journal of Metrology and Quality Engineering, 2012 We consider the comparative calibration problem in the case when linear relationship is assumed between two considered measuring devices with possibly different units and precisions.
Wimmer G., Witkovský V.
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An Overview of Linear Structural Models in Errors in Variables Regression
Revstat Statistical Journal, 2010 This paper aims to overview the numerous approaches that have been developed to estimate the parameters of the linear structural model. The linear structural model is an example of an errors in variables model, or measurement error model that has wide ...
Jonathan Gillard
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Beta regression model nonlinear in the parameters with additive measurement errors in variables.
PLoS ONE, 2021 We propose in this paper a general class of nonlinear beta regression models with measurement errors. The motivation for proposing this model arose from a real problem we shall discuss here. The application concerns a usual oil refinery process where the
Daniele de Brito Trindade +4 more
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Mathematics, 2020 In regression analysis, oftentimes a linear (or linearized) Gauss-Markov Model (GMM) is used to describe the relationship between certain unknown parameters and measurements taken to learn about them.
Burkhard Schaffrin
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Asymptotic normality of total least squares estimator in a multivariate errors-in-variables model
Modern Stochastics: Theory and Applications, 2016 We consider a multivariate functional measurement error model $AX\approx B$. The errors in $[A,B]$ are uncorrelated, row-wise independent, and have equal (unknown) variances.
Alexander Kukush +1 more
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