Results 21 to 30 of about 8,978,880 (312)
Open Mathematics, 2020 In this article, an errors-in-variables regression model in which the errors are negatively superadditive dependent (NSD) random variables is studied. First, the Marcinkiewicz-type strong law of large numbers for NSD random variables is established. Then,
Zhang Yu +3 more
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Structural Measurement Errors in Nonseparable Models [PDF]
, 2009 This paper considers measurement error from a new perspective. In surveys, response errors are often caused by the fact that respondents recall past events and quantities imperfectly.
Winter, Joachim, Hoderlein, Stefan
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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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Empirical Likelihood Confidence Region for Parameters in Semi-linear Errors-in-Variables Models [PDF]
, 2006 This paper proposes a constrained empirical likelihood confidence region for a parameter in the semi-linear errors-in-variables model. The confidence region is constructed by combining the score function corresponding to the squared orthogonal distance
Kong, Efang, Cui, Hengjian
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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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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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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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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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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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