Sparse Multivariate Analysis Reveals Dissociable White Matter Networks for Cognitive and Motor Processing Speed [PDF]
Brain SciencesBackground: Reaction time (RT) is a fundamental measure of information processing speed in cognitive neuroscience and is influenced by both structural and functional brain properties.
Shahwar Yasir +6 more
doaj +2 more sources
AI-Carbon-Energy: Spillover effects and drivers in interconnected markets [PDF]
iScienceSummary: This study explores the spillover effects between the AI market, international carbon market, and energy markets based on a time-varying parameter vector autoregression model.
Mingming Zhang +3 more
doaj +2 more sources
A multiparameter diagnostic model based on MRI volumetric ADC histogram and clinical variables accurately differentiates thymic epithelial tumors from mediastinal lymphomas [PDF]
BMC Medical ImagingBackground The management and prognosis of each type of anterior mediastinal mass differ substantially. Radical thymectomy is regarded as the preferred surgical approach for resectable thymic epithelial tumors (TETs), whereas chemotherapy is the ...
Luna Wang +5 more
doaj +2 more sources
On Multivariate Skewness and Kurtosis [PDF]
Sankhya A, 2020 AbstractA unified treatment of all currently available cumulant-based indexes of multivariate skewness and kurtosis is provided here, expressing them in terms of the third and fourth-order cumulant vectors respectively. Such a treatment helps reveal many subtle features and inter-connections among the existing indexes as well as some deficiencies ...
Jammalamadaka, Sreenivasa Rao +2 more
openaire +3 more sources
Comparison of normality test methods for some soil properties in the arid land of South Khorasan. [PDF]
Desert, 2023 Statistical assumptions are the basis of many univariate and multivariate statistical tests. Normality is the most basic assumption of multivariate analysis in plant ecology.
M. Rostampour, F. Azarmi-Atajan
doaj +1 more source
More on the Supremum Statistic to Test Multivariate Skew-Normality
Computation, 2021 This review is about verifying and generalizing the supremum test statistic developed by Balakrishnan et al. Exhaustive simulation studies are conducted for various dimensions to determine the effect, in terms of empirical size, of the supremum test ...
Timothy Opheim, Anuradha Roy
doaj +1 more source
Some Statistical Aspects of the Truncated Multivariate Skew-t Distribution
Mathematics, 2022 The multivariate skew-t distribution plays an important role in statistics since it combines skewness with heavy tails, a very common feature in real-world data.
Raúl Alejandro Morán-Vásquez +2 more
doaj +1 more source
Mathematics, 2021 Non-normality is a usual fact when dealing with gene expression data. Thus, flexible models are needed in order to account for the underlying asymmetry and heavy tails of multivariate gene expression measures.
Jorge M. Arevalillo, Hilario Navarro
doaj +1 more source
On a Vector-Valued Measure of Multivariate Skewness [PDF]
Symmetry, 2021 The canonical skewness vector is an analytically simple function of the third-order, standardized moments of a random vector. Statistical applications of this skewness measure include semiparametric modeling, independent component analysis, model-based clustering, and multivariate normality testing.
openaire +3 more sources
Fast inference methods for high-dimensional factor copulas
Dependence Modeling, 2022 Gaussian factor models allow the statistician to capture multivariate dependence between variables. However, they are computationally cumbersome in high dimensions and are not able to capture multivariate skewness in the data.
Verhoijsen Alex, Krupskiy Pavel
doaj +1 more source