Results 51 to 60 of about 16,146 (162)

Adaptive Segmentation and Statistical Analysis for Multivariate Big Data Forecasting

Big Data and Cognitive Computing
Forecasting high-volume, univariate, and multivariate longitudinal data streams is a critical challenge in Big Data systems, especially with constrained computational resources and pronounced data variability.
Desmond Fomo, Aki-Hiro Sato
doaj   +1 more source

Assessment of survival in patients with idiopathic pulmonary fibrosis using quantitative HRCT indexes

Multidisciplinary Respiratory Medicine, 2018
Background The assessment of Idiopathic Pulmonary Fibrosis (IPF) using HRCT requires great experience and is limited by a significant inter-observer variability, even between trained radiologists.
Sebastiano Emanuele Torrisi, Stefano Palmucci, Alessandro Stefano, Giorgio Russo, Alfredo Gaetano Torcitto, Daniele Falsaperla, Mauro Gioè, Mauro Pavone, Ada Vancheri, Gianluca Sambataro, Domenico Sambataro, Letizia Antonella Mauro, Emanuele Grassedonio, Antonio Basile, Carlo Vancheri   +14 more
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Posterior Analysis of State Space Model with Spherical Symmetricity

Journal of Probability and Statistics, 2015
The present work investigates state space model with nonnormal disturbances when the deviation from normality has been observed only with respect to kurtosis and the distribution of disturbances continues to follow a symmetric family of distributions ...
Ranjita Pandey
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Normrank Correlations for Testing Associations and for Use in Latent Variable Models

Open Education Studies
Pearson’s correlation is widely used to test for an association between two variables and also forms the basis of several multivariate statistical procedures including many latent variable models. Spearman’s ρ\rho is a popular alternative.
Wright Daniel B.
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A Multivariate Skew-Normal Mean-Variance Mixture Distribution and Its Application to Environmental Data with Outlying Observations

Journal of Statistical Theory and Applications (JSTA)
The presence of outliers, skewness, kurtosis, and dependency are well-known challenges while fitting distributions to many data sets. Developing multivariate distributions that can properly accomodate all these aspects has been the aim of several ...
M. Tamandi, N. Balakrishnan, A. Jamalizadeh, M. Amiri   +3 more
doaj   +1 more source

The value of diffusion kurtosis imaging to predict early radiotherapy response in nasopharyngeal carcinoma patients

Zhongguo aizheng zazhi, 2018
Background and purpose: Magnetic resonance imaging (MRI) diffusion kurtosis imaging (DKI) is a new non-invasive functional imaging technology, which is the extension and development of diffusion tensor imaging (DTI) technology.
吴　刚, 王　奋, 林少民
doaj  

Hessian Stochastic Ordering in the Family of multivariate Generalized Hyperbolic Distributions and its Applications

پژوهش‌های ریاضی, 2022
In this paper, random vectors following the multivariate generalized hyperbolic (GH) distribution are compared using the hessian stochastic order. This family includes the classes of symmetric and asymmetric distributions by which different behaviors of ...
Mehdi Amiri, Ahad Jamalizadeh, Salman Izadkhah   +2 more
doaj  

Prognostic Value of Pre‐Treatment Diffusion Kurtosis Imaging for Progression‐Free Survival Prediction in Advanced Nasopharyngeal Carcinoma

Cancer Medicine
Purpose This study aimed to evaluate the value of diffusion kurtosis imaging (DKI) for prognostic value for long‐term PFS in nasopharyngeal carcinoma (NPC).
Wang Ren, Xiang Zheng, Shizhong Wu, Caixia Wu, Dechun Zheng   +4 more
doaj   +1 more source

Multivariate skewness and kurtosis measures with an application in ICA

Journal of Multivariate Analysis, 2008
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Tests Based on Skewness and Kurtosis for Multivariate Normality

Communications for Statistical Applications and Methods, 2015
A measure of skewness and kurtosis is proposed to test multivariate normality. It is based on an empirical standardization using the scaled residuals of the observations. First, we consider the statistics that take the skewness or the kurtosis for each coordinate of the scaled residuals.
openaire   +2 more sources