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A General Solution for the Errors in Variables (EIV) Model with Equality and Inequality Constraints
Applied Sciences, 2022 Targeting the adjustment of the errors-in-variables (EIV) model with equality and inequality constraints, a general solution that is similar to the classical least square adjustment is proposed based on the penalty function and the weight in measurement.
Dengshan Huang, Yulin Tang, Qisheng Wang
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Errors-in-Variables Models [PDF]
, 2000 Errors-in-variables (EIV) models axe regression models in which the regres-sors axe observed with errors. These models include the linear EIV models, the nonlinear EIV models, and the partially linear EIV models. Suppose that we want to investigate the relationship between the yield (Y) of corn and available nitrogen (X) in the soil.
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The Astrophysical Journal, 2023 Galaxy stellar mass is known to be monotonically related to the size of the galaxy’s globular cluster (GC) population for Milky Way sized and larger galaxies.
Samantha C. Berek +3 more
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Errors in variables in simultaneous equation models [PDF]
Journal of Econometrics, 1977 Abstract The simultaneous equation model is considered when errors in variables are present in the exogenous variables. By means of a distributional assumption on the exogenous variables, the system is transformed into an augmented structural model.
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Likelihood Inference in the Errors-in-Variables Model
Journal of Multivariate Analysis, 1996 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Murphy, S.A., Van Der Vaart, A.W.
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NeuroImage, 2020 Comparing electric field simulations from individualized head models against in-vivo intra-cranial recordings is considered the gold standard for direct validation of computational field modeling for transcranial brain stimulation and brain mapping ...
Oula Puonti +3 more
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Estimation of Nonlinear Errors-in-Variables Models
The Annals of Statistics, 1982 An estimation procedure is presented for the coefficients of the nonlinear functional relation, where observations are subject to measurement error. The distributional properties of the estimators are derived, and a consistent estimator of the covariance matrix is given.
Wolter, Kirk M., Fuller, Wayne A.
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Scaled weighted total least-squares adjustment for partial errors-in-variables model
Journal of Geodetic Science, 2016 Scaled total least-squares (STLS) unify LS, Data LS, and TLS with a different choice of scaled parameter. The function of the scaled parameter is to balance the effect of random error of coefficient matrix and observation vector for the estimate of ...
Zhao J.
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Journal of Inequalities and Applications, 2020 In this paper, we estimate the mean of the partially linear single-index errors-in-variables model with missing response variables. The linear covariate is measured with additive error, therefore missing is not random.
Xin Qi, ZhuoXi Yu
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Consistency of the total least squares estimator in the linear errors-in-variables regression
Modern Stochastics: Theory and Applications, 2018 This paper deals with a homoskedastic errors-in-variables linear regression model and properties of the total least squares (TLS) estimator. We partly revise the consistency results for the TLS estimator previously obtained by the author [18]. We present
Sergiy Shklyar
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