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The usefulness of robust multivariate methods: A case study with the menu items of a fast food restaurant chain
(Universidade Federal de Santa Maria, 2020)
Dimensionality reduction for visualization of normal and pathological speech data
(Elsevier, 2009-07)
For an adequate analysis of pathological speech signals, a sizeable number of parameters is required, such as those related to jitter, shimmer and noise content. Often this kind of high-dimensional signal representation ...
Improving the precision matrix for precision cosmology
(Oxford University Press, 2015-12)
The estimation of cosmological constraints from observations of the large-scale structure of the Universe, such as the power spectrum or the correlation function, requires the knowledge of the inverse of the associated ...
Comparative study of extracellular recording methods for analysis of afferent sensory information: Empirical modeling, data analysis and interpretation
(Elsevier B.V., 2019-05)
Background: Physiological studies of sensorial systems often require the acquisition and processing of data extracted from their multiple components to evaluate how the neural information changes in relation to the environment ...
A review of multivariate calibration methods applied to biomedical analysis
(Elsevier Science, 2006-01)
The determination of the contents of therapeutic drugs, metabolites and other important biomedical analytes in biological samples is usually performed by using high-performance liquid chromatography (HPLC). Modern multivariate ...
The evolution of the observed Hubble sequence over the past 6GYR
(2010-11-01)
During the past years we have confronted serious problems of methodology concerning the morphological and kinematic classification of distant galaxies. This has forced us to create a new simple and effective morphological ...
A review of innovation-based methods to jointly estimate model and observation error covariance matrices in ensemble data assimilation
(Amer Meteorological Soc, 2020-10)
Data assimilation combines forecasts from a numerical model with observations. Most of the current data assimilation algorithms consider the model and observation error terms as additive Gaussian noise, specified by their ...
Automatic seabed classification using functional data analysis and time series cluster techniques
(Universidad de Valencia, 2016)
Seabed characterization in coastal environments is usually based on acoustic techniques. Since intrusive measurements are very time-consuming, data acquired by echosounders are the best option for classification purposes. ...
Functional data analysis, a new approach to aligning three-way liquid chromatographic with fluorescence detection data
(Elsevier Science, 2018-11)
Functional data analysis (FDA) arises as a promissory auxiliary methodology designed to help the analytical chemists, especially chemometricians. However, although the innovative ideas of this approach have barely spread ...