Results 21 to 30 of about 117,319,651 (289)
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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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
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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
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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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On errors-in-variables estimation with unknown noise variance ratio
, 2006 We propose an estimation method for an errors-in-variables model with unknown input and output noise variances. The main assumption that allows identifiability of the model is clustering of the data into two clusters that are distinct in a certain ...
Van Huffel, S. +2 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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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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Ecosphere, 2019 Conservation planning for wildlife species requires mapping and assessment of habitat suitability across broad areas, often relying on a diverse suite, or stack, of geospatial data presenting multidimensional controls on a species.
Emilie B. Henderson +2 more
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Multivariate models to classify Tuscan virgin olive oils by zone.
Grasas y Aceites, 1999 In order to study and classify Tuscan virgin olive oils, 179 samples were collected. They were obtained from drupes harvested during the first half of November, from three different zones of the Region. The sampling was repeated for 5 years. Fatty acids,
Stefano Alessandri +4 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
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