Results 31 to 40 of about 2,060,595 (185)
Revisiting Guerry's data: Introducing spatial constraints in multivariate analysis
, 2011 Standard multivariate analysis methods aim to identify and summarize the main structures in large data sets containing the description of a number of observations by several variables.
Dray, Stéphane, Jombart, Thibaut
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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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Posterior mean and variance approximation for regression and time series problems [PDF]
, 2008 This paper develops a methodology for approximating the posterior first two moments of the posterior distribution in Bayesian inference. Partially specified probability models that are defined only by specifying means and variances, are constructed based
Harrison, P.J., Triantafyllopoulos, K.
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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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Sensors, 2020 New instruments to characterize vegetation must meet cost constraints while providing accurate information. In this paper, we study the potential of a laser speckle system as a low-cost solution for non-destructive phenotyping. The objective is to assess
Maxime Ryckewaert +9 more
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Multivariate Statistical Analysis of Phyllite Samples Based on Chemical (XRF) and Mineralogical Data by XRD [PDF]
, 2012 It is presented the results obtained of a multivariate statistical analysis concerning the chemical and phase composition, as a characterization purpose, carried out with 52 rock phyllite samples selected from the provinces of Almería and Granada (SE ...
Garzón Garzón, Eduardo +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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Molecules, 2020 The last two decades have witnessed an increasing interest in the use of the so-called rapid analytical methods or high throughput techniques. Most of these applications reported the use of vibrational spectroscopy methods (near infrared (NIR), mid ...
Daniel Cozzolino
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Covariance pattern mixture models for the analysis of multivariate heterogeneous longitudinal data
, 2015 We propose a novel approach for modeling multivariate longitudinal data in the presence of unobserved heterogeneity for the analysis of the Health and Retirement Study (HRS) data.
Anderlucci, Laura, Viroli, Cinzia
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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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