Consumer preferences and purchasing rationales for wine: a multivariate data analysis
New Medit, 2020 The wine market is very heterogeneous and complex, being the knowledge of the behaviour and attitudes of consumers a key tool to design efficient marketing plans, namely in countries that are traditionally wine producers and consumers, such as Portugal ...
Carla Ferreira +5 more
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A whitening approach to probabilistic canonical correlation analysis for omics data integration
BMC Bioinformatics, 2019 Background Canonical correlation analysis (CCA) is a classic statistical tool for investigating complex multivariate data. Correspondingly, it has found many diverse applications, ranging from molecular biology and medicine to social science and finance.
Takoua Jendoubi, Korbinian Strimmer
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Multivariate analysis of flow cytometric data using decision trees
Frontiers in Microbiology, 2012 Characterization of the response of the host immune system is important in understanding the bidirectional interactions between the host and microbial pathogens.
Svenja eSimon +5 more
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Factor Analysis Biplots for Continuous, Binary and Ordinal Data
StatsThis article presents biplots derived from factor analysis of correlation matrices for both continuous and ordinal data. It introduces biplots specifically designed for factor analysis, detailing the geometric interpretation for each data type and ...
Marina Valdés-Rodríguez +2 more
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Comparative Metabolomics Analysis of Weedy Rice (Oryza spp.) across Peninsular Malaysia
Agriculture, 2023 Weedy rice (Oryza spp.) is a notorious weed that invades paddy fields and hampers the rice’s production and yield quality; thus, it has become a major problem for rice farmers worldwide. Weedy rice comprises a diverse morphology and phenotypic variation;
Intan Filzah Mahmod +5 more
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MVApp—Multivariate Analysis Application for Streamlined Data Analysis and Curation1[OPEN]
Plant Physiology, 2019 MVApp offers a free and collaborative platform for streamlined curation and analysis of plant phenotyping datasets. Modern phenotyping techniques yield vast amounts of data that are challenging to manage and analyze.
M. Julkowska +7 more
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Modeling of Biomass Gasification: From Thermodynamics to Process Simulations
Energies, 2023 Biomass gasification has obtained great interest over the last few decades as an effective and trustable technology to produce energy and fuels with net-zero carbon emissions.
Vera Marcantonio +3 more
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CLUSTER ANALYSIS OF MULTIVARIATE PANEL DATA ON DATA CONTAINING OUTLIERS
BarekengOne clustering method for panel data is K-Means Longitudinal (KML), which considers only a single trajectory per subject over time. To address this limitation, KML was extended into K-Means Longitudinal 3D (KML3D), which enables clustering of joint or ...
Kristuisno Martsuyanto Kapiluka +2 more
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A co-analysis framework for exploring multivariate scientific data
Visual Informatics, 2018 In complex multivariate data sets, different features usually include diverse associations with different variables, and different variables are associated within different regions.
Xiangyang He +3 more
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Metabolic profiling of body fluids and multivariate data analysis
MethodsX, 2017 Metabolome analyses of body fluids are challenging due pre-analytical variations, such as pre-processing delay and temperature, and constant dynamical changes of biochemical processes within the samples.
Jean-Pierre Trezzi +6 more
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