Results 11 to 20 of about 452,503 (268)
Consistent estimation in the bilinear multivariate errors-in-variables model [PDF]
Metrika, 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
Kukush, A. +2 more
openaire +4 more sources
A multivariate ultrastructural errors-in-variables model with equation error
Journal of Multivariate Analysis, 2011 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Patriota, Alexandre G. +2 more
openaire +7 more sources
Assimilating GlobColour ocean colour data into a pre-operational physical-biogeochemical model [PDF]
Ocean Science, 2012 As part of the GlobColour project, daily chlorophyll <i>a</i> observations, derived using remotely sensed ocean colour data from the MERIS, MODIS and SeaWiFS sensors, are produced.
D. A. Ford +5 more
doaj +1 more source
Sensors, 2022 Ultrasound imaging (US) is a widely used imaging tool in physiotherapy for assessing muscle morphology and quality, among other purposes, such as ensuring the patients’ safety during invasive procedures or providing visual feedback during motor control ...
Juan Antonio Valera-Calero +4 more
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Generalized background error covariance matrix model (GEN_BE v2.0) [PDF]
Geoscientific Model Development, 2015 The specification of state background error statistics is a key component of data assimilation since it affects the impact observations will have on the analysis.
G. Descombes +4 more
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Forecasting, 2021 This paper examines the suitability of Google Trends data for the modeling and forecasting of interregional migration in Russia. Monthly migration data, search volume data, and macro variables are used with a set of univariate and multivariate models to ...
Dean Fantazzini +3 more
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Estimation in multivariate errors-in-variables models
Linear 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.
Chan, N.N., Mak, T.K.
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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
doaj +1 more source
Optimality of Quasi-Score in the multivariate mean-variance model with an application to the zero-inflated Poisson model with measurement errors [PDF]
, 2006 In a multivariate mean-variance model, the class of linear score (LS) estimators based on an unbiased linear estimating function is introduced. A special member of this class is the (extended) quasi-score (QS) estimator.
Kukush, Alexander +3 more
core +1 more source
Predicting seasonal influenza transmission using functional regression models with temporal dependence. [PDF]
PLoS ONE, 2018 This paper proposes a novel approach that uses meteorological information to predict the incidence of influenza in Galicia (Spain). It extends the Generalized Least Squares (GLS) methods in the multivariate framework to functional regression models with ...
Manuel Oviedo de la Fuente +3 more
doaj +1 more source