Asymptotic normality of element-wise weighted total least squares estimator in a multivariate errors-in-variables model [PDF]
Inaccuracies were corrected. In the score function appeared a new factor that independent of observations. All theorems remained unchanged.
Yaroslav Tsaregorodtsev
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Correcting the estimator for the mean vectors in a multivariate errors-in-variables regression model [PDF]
The multivariate errors-in-variables regression model is applicable when both dependent and independent variables in a multivariate regression are subject to measurement errors. In such a scenario it is long established that the traditional least squares approach to estimating the model parameters is biased and inconsistent.
Johannes F. Lutzeyer, Edward A. K. Cohen
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Consistency of the structured total least squares estimator in a multivariate errors-in-variables model [PDF]
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Alexander Kukush +2 more
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Simulating model uncertainty of subgrid-scale processes by sampling model errors at convective scales [PDF]
Ideally, perturbation schemes in ensemble forecasts should be based on the statistical properties of the model errors. Often, however, the statistical properties of these model errors are unknown. In practice, the perturbations are pragmatically modelled
M. Van Ginderachter +6 more
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Estimation in multivariate errors-in-variables models
This paper reviews and extends some of the known results in the estimation in ''errors-in-variables'' models, treating the structural and the functional cases on a unified basis. The generalized least-squares method proposed by some previous authors is extended to the case where the error covariance matrix contains an unknown vector parameter.
N. N. Chan, Tak K. Mak
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Consistent estimation in the bilinear multivariate errors-in-variables model [PDF]
A bilinear multivariate errors-in-variables model is considered. It corresponds to an overdetermined set of linear equations AXB=C, A?Rm×n, B?Rp×q, in which the data A, B, C are perturbed by errors. The total least squares estimator is inconsistent in this case. An adjusted least squares estimator hat X is constructed, which converges to the true value
Alexander Kukush +2 more
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Generalized least squares estimation of the functional multivariate linear errors-in-variables model
The method of generalized least squares is applied to the sample matrix of mean squares and products to obtain estimators of the parameters of the functional multivariate linear errors-in-variables model. These estimators are shown to be consistent and asymptotically multivariate normal. Relationships between generalized least squares estimation of the
P.Fred Dahm, Wayne A. Fuller
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Erratum to “Asymptotic normality of total least squares estimator in a multivariate errors-in-variables model $AX = B$” [PDF]
Alexander Kukush +1 more
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Estimation of the parameters of the multivariate linear errors in variables model
Paul Frederick Dahm
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Fitting an Equation to Data Impartially
We consider the problem of fitting a relationship (e.g., a potential scientific law) to data involving multiple variables. Ordinary (least squares) regression is not suitable for this because the estimated relationship will differ according to which ...
Chris Tofallis
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