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
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Multivariate Wind Turbine Power Curve Model Based on Data Clustering and Polynomial LASSO Regression
Applied Sciences, 2021 Wind turbine performance monitoring is a complex task because of the non-stationary operation conditions and because the power has a multivariate dependence on the ambient conditions and working parameters.
Davide Astolfi, Ravi Pandit
doaj +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
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ARX Model Estimation of Multivariable Errors-in-Variables Systems
IFAC-PapersOnLine, 2018 Abstract This paper proposes a method for the estimation of ARX (Autoregressive with external input) model of multivariable errors-in-variables (EIV) systems. In parameter estimation, the input noise variances need to be estimated in order to obtain a consistent estimate. Two methods are developed to estimate the input noises variances. One way is to
Xin Liu, Yucai Zhu
openaire +1 more source
Multivariate calibration and moisture control in yerba mate by near infrared spectroscopy
Acta Scientiarum: Technology, 2014 This work describes the development of a multivariate model based on near infrared reflectance spectroscopy (NIR) and partial least squares regression for the prediction of the moisture content in yerba mate samples.
Larize Mazur +5 more
doaj +1 more source
BMC Medical Research Methodology, 2023 Background In medical, social, and behavioral research we often encounter datasets with a multilevel structure and multiple correlated dependent variables.
Xynthia Kavelaars +2 more
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Multivariate small sample tests for two-way designs with applications to industrial statistics [PDF]
, 2018 In this paper, we present a novel nonparametric approach for multivariate analysis of two-way crossed factorial design based on NonParametric Combination applied to Synchronized Permutation tests.
Arboretti, Rosa +4 more
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Univariate and multivariate nonlinear models in productive traits of the sunn hemp
Revista Ciência Agronômica, 2020 Multivariate analysis helps to understand the relationships between dependent variables; this methodology has great potential in several areas of knowledge.
Cláudia Marques de Bem +3 more
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Química Nova, 2011 A multivariate spectrophotometric method was developed for analysis of kojic acid/hydroquinone associations in skin whitening cosmetics. The method is based on the reaction between kojic acid and Fe3+ and on the reduction of Fe3+ by hydroquinone and ...
Giselle Nathaly Calaça +2 more
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ENSO-ASC 1.0.0: ENSO deep learning forecast model with a multivariate air–sea coupler [PDF]
Geoscientific Model Development, 2021 The El Niño–Southern Oscillation (ENSO) is an extremely complicated ocean–atmosphere coupling event, the development and decay of which are usually modulated by the energy interactions between multiple physical variables.
B. Mu, B. Qin, S. Yuan
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