Results 21 to 30 of about 467,233 (256)
, 2017 In many problems from multivariate analysis, the parameter of interest is a shape matrix, that is, a normalized version of the corresponding scatter or dispersion matrix.
Paindaveine, Davy, Van Bever, Germain
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Frontiers in Neurology, 2022 AimsThis study aimed to build a prediction model to early diagnose intracranial atherosclerosis (ICAS)-related large vascular occlusion (LVO) in acute ischemic stroke patients before digital subtractive angiography.MethodsPatients enrolled in the DIRECT ...
He Li +12 more
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Comparison of Some Multivariate Nonparametric Tests in Profile Analysis to Repeated Measurements [PDF]
, 2016 Through Monte Carlo simulations, the performance of six multivariate nonparametric tests for testing the hypothesis of parallelism in profile analysis was studied.
Sadeghi, Erfan +2 more
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The Investigation of the Relationship Between Growth Type and Capital Structure of Firms [PDF]
راهبرد مدیریت مالی, 2016 The purpose of this study was to investigation the relationship between growth type and capital structure of listed firms in Tehran Stock Exchange. For this purpose, the firms are classified in to three groups low, mix and high growth and statistical ...
Omid Pourheydari +4 more
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Wind turbine condition monitoring strategy through multiway PCA and multivariate inference [PDF]
, 2018 This article states a condition monitoring strategy for wind turbines using a statistical data-driven modeling approach by means of supervisory control and data acquisition (SCADA) data. Initially, a baseline data-based model is obtained from the healthy
Pozo Montero, Francesc +2 more
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Variability of eight Polish populations of Pinus sylvestris L. expressed in traits of cones
Acta Societatis Botanicorum Poloniae, 2014 Two-year old cones were collected from 257 standing Pinus sylvestris L. trees, representing 8 Polish populations of the species. The cones were analyzed in respect to 11 morphological traits.
Maria A. Bobowicz, Adolf F. Korczyk
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CLT for eigenvalue statistics of large-dimensional general Fisher matrices with applications [PDF]
, 2017 Random Fisher matrices arise naturally in multivariate statistical analysis and understanding the properties of its eigenvalues is of primary importance for many hypothesis testing problems like testing the equality between two covariance matrices, or ...
Bai, Z, Yao, JJ, Zheng, S
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Multivariate search for differentially expressed gene combinations
BMC Bioinformatics, 2004 Background To identify differentially expressed genes, it is standard practice to test a two-sample hypothesis for each gene with a proper adjustment for multiple testing. Such tests are essentially univariate and disregard the multidimensional structure
Klebanov Lev +4 more
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A new test for the mean vector in high-dimensional data [PDF]
Songklanakarin Journal of Science and Technology (SJST), 2015 For the testing of the mean vector where the data are drawn from a multivariate normal population, the renowned Hotelling’s T 2 test is no longer valid when the dimension of the data equals or exceeds the sample size.
Knavoot Jiamwattanapong +1 more
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MATS: Inference for potentially Singular and Heteroscedastic MANOVA [PDF]
, 2017 In many experiments in the life sciences, several endpoints are recorded per subject. The analysis of such multivariate data is usually based on MANOVA models assuming multivariate normality and covariance homogeneity.
Friedrich, Sarah, Pauly, Markus
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