Results 1 to 10 of about 2,619,530 (217)
Journal of Hazardous Materials, 2021 Industrial sites affected by anthropogenic contamination, both past and present-day, commonly have intricate pollutant patterns, and source discrimination can be thus highly challenging.
D. Baragaño +5 more
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On the usage of joint diagonalization in multivariate statistics
Journal of Multivariate Analysis, 2021 Scatter matrices generalize the covariance matrix and are useful in many multivariate data analysis methods, including well-known principal component analysis (PCA), which is based on the diagonalization of the covariance matrix.
K. Nordhausen, A. Ruiz-Gazen
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Statistical Picking of Multivariate Waveforms
Sensors, 2022 In this paper, we propose a new approach based on the fitting of a generalized linear regression model in order to detect points of change in the variance of a multivariate-covariance Gaussian variable, where the variance function is piecewise constant.
Nicoletta D'Angelo +3 more
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Choosing Among Notions of Multivariate Depth Statistics [PDF]
Statistical Science, 2020 Classical multivariate statistics measures the outlyingness of a point by its Mahalanobis distance from the mean, which is based on the mean and the covariance matrix of the data.
K. Mosler, Pavlo Mozharovskyi
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TRANSFORMATIONS FOR MULTIVARIATE STATISTICS [PDF]
Econometric Theory, 2004 Summary: This paper derives transformations for multivariate statistics that eliminate asymptotic skewness, extending results of \textit{N. Niki} and \textit{S. Konishi} [Ann. Inst. Stat. Math. 38, 371--383 (1986; Zbl 0609.62075)]. Within the context of valid Edgeworth expansions for such statistics we first derive the set of equations that such a ...
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Assessment of plant biomass for pellet production using multivariate statistics (PCA and HCA)
Renewable Energy, 2019 Multivariate statistics can be a powerful tool in the assessment of energy properties of lignocellulosic materials and it is fundamental to estimate the theoretical, technical and economic potentials of these biomasses for bioenergy production.
Dorival Pinheiro Garcia +4 more
semanticscholar +1 more source
Wildfire Probability Mapping: Bivariate vs. Multivariate Statistics
Remote Sensing, 2019 Wildfires are one of the most common natural hazards worldwide. Here, we compared the capability of bivariate and multivariate models for the prediction of spatially explicit wildfire probability across a fire-prone landscape in the Zagros ecoregion ...
A. Jaafari, D. Gholami, B. Pham, D. Bui
semanticscholar +1 more source
Water Science, 2016 This study investigates the groundwater quality in the Faridpur district of central Bangladesh based on preselected 60 sample points. Water evaluation indices and a number of statistical approaches such as multivariate statistics and geostatistics are ...
M. Bodrud-Doza +5 more
semanticscholar +1 more source