Results 11 to 20 of about 451,504 (196)

Asymptotic normality of element-wise weighted total least squares estimator in a multivariate errors-in-variables model [PDF]

open access: green, 2017
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]

open access: green, 2015
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
openalex   +3 more sources

Consistency of the structured total least squares estimator in a multivariate errors-in-variables model [PDF]

open access: closedJournal of Statistical Planning and Inference, 2004
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Alexander Kukush   +2 more
openalex   +5 more sources

Simulating model uncertainty of subgrid-scale processes by sampling model errors at convective scales [PDF]

open access: yesNonlinear Processes in Geophysics, 2020
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
doaj   +4 more sources

Estimation in multivariate errors-in-variables models

open access: closedLinear Algebra and its Applications, 1985
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
openalex   +3 more sources

Consistent estimation in the bilinear multivariate errors-in-variables model [PDF]

open access: closedMetrika, 2003
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
openalex   +3 more sources

Generalized least squares estimation of the functional multivariate linear errors-in-variables model

open access: closedJournal of Multivariate Analysis, 1986
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
openalex   +3 more sources

Fitting an Equation to Data Impartially

open access: yesMathematics, 2023
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
doaj   +1 more source

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