Asymptotic normality of total least squares estimator in a multivariate errors-in-variables model [PDF]
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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Goodness-of-fit test in a multivariate errors-in-variables model [PDF]
Modern Stochastics: Theory and Applications, 2016 We consider a multivariable functional errors-in-variables model $AX\approx B$, where the data matrices A and B are observed with errors, and a matrix parameter X is to be estimated.
Alexander Kukush +1 more
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Fast and robust estimation of the multivariate errors in variables model [PDF]
TEST, 2009 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Christophe Croux +2 more
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Adjusted likelihood inference in an elliptical multivariate\n errors-in-variables model [PDF]
Communications in Statistics - Theory and Methods, 2011 In this paper we obtain an adjusted version of the likelihood ratio test for errors-in-variables multivariate linear regression models. The error terms are allowed to follow a multivariate distribution in the class of the elliptical distributions, which has the multivariate normal distribution as a special case.
Tatiane F. N. Melo, Silvia L. P. Ferrari
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Estimation in a Multivariate "Errors in Variables" Regression Model: Large Sample Results [PDF]
The Annals of Statistics, 1981 In a multivariate "errors in variables" regression model, the unknown mean vectors $\mathbf{u}_{1i}: p \times 1, \mathbf{u}_{2i}: r \times 1$ of the vector observations $\mathbf{x}_{1i}, \mathbf{x}_{2i}$, rather than the observations themselves, are assumed to follow the linear relation: $\mathbf{u}_{2i} = \alpha + B\mathbf{u}_{1i}, i = 1,2,\cdots, n$.
Leon Jay Gleser
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Estimation for the Multivariate Errors-in-Variables Model with Estimated Error Covariance Matrix [PDF]
The Annals of Statistics, 1984 The authors consider the estimation problem of multivariate errors-in- variables models. Let \(r\times 1\) row vectors \(y_ i\) and \(k\times 1\) row vectors \(x_ i\) satisfy \(y_ i=\beta_ 0+x_ i\beta\), \(i=1,2,...,n\), where \(\beta_ 0\) and \(\beta\) are 1\(\times r\) and \(k\times r\) matrices of parameters, respectively.
Yasuo Amemiya, Wayne A. Fuller
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New multivariate central limit theorems in linear structural and functional error-in-variables models [PDF]
Electronic Journal of Statistics, 2007 This paper deals simultaneously with linear structural and functional error-in-variables models (SEIVM and FEIVM), revisiting in this context generalized and modified least squares estimators of the slope and intercept, and some methods of moments estimators of unknown variances of the measurement errors.
Yuliya V. Martsynyuk
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A multivariate ultrastructural errors-in-variables model with equation error
Journal of Multivariate Analysis, 2010 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Alexandre G. Patriota +2 more
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The asymptotic normality of an adjusted least squares estimator in a multivariate vector errors-in-variables regression model [PDF]
Theory of Probability and Mathematical Statistics, 2014 Summary: An adjusted least squares estimator in a linear multivariate vector error-in-variables regression model is considered in this paper. Conditions for the asymptotic normality of this estimator are given. A modification of the estimator is constructed whose asymptotic properties are the same as those of the adjusted least squares estimator and ...
I. O. Sen’ko
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Bayesian Analysis of a Multivariate Null Intercept Errors-in-Variables Regression Model
Journal of Biopharmaceutical Statistics, 2003 Longitudinal data are of great interest in analysis of clinical trials. In many practical situations the covariate can not be measured precisely and a natural alternative model is the errors-in-variables regression models. In this paper we study a null intercept errors-in-variables regression model with a structure of dependency between the response ...
Reiko Aoki +3 more
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