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Statistical Applications of the Multivariate Skew Normal Distribution
Journal of the Royal Statistical Society Series B: Statistical Methodology, 1999 Summary Azzalini and Dalla Valle have recently discussed the multivariate skew normal distribution which extends the class of normal distributions by the addition of a shape parameter. The first part of the present paper examines further probabilistic properties of the distribution, with special emphasis on aspects of statistical ...
AZZALINI, ADELCHI, CAPITANIO A.
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A block EM algorithm for multivariate skew normal and skew t-mixture models
IEEE transactions on neural networks and learning systems, 2016 Finite mixtures of skew distributions provide a flexible tool for modelling heterogeneous data with asymmetric distributional features. However, parameter estimation via the Expectation-Maximization (EM) algorithm can become very time-consuming due to the complicated expressions involved in the E-step that are numerically expensive to evaluate.
Sharon X. Lee +2 more
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The role of temporal abundance structure and habitat preferences in the survival of conodonts during the mid-early Silurian Ireviken mass extinction event. [PDF]
PLoS ONE, 2015 The Ireviken event was one of the most intense extinction episodes that occurred during the mid-Paleozoic era. It had a strong global effect on a range of clades, with conodonts, graptolites and chitinozoans affected most.
Andrej Spiridonov +2 more
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Scientific ReportsWe examined the association between texture features using three-dimensional (3D) io-dine density histogram on delayed phase of dual-energy CT (DECT) and expression of programmed death-ligand 1 (PD-L1) using immunostaining methods in non-small cell lung ...
Kazuki Yamagata +8 more
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Adaptive Segmentation and Statistical Analysis for Multivariate Big Data Forecasting
Big Data and Cognitive ComputingForecasting 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
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Estimation of the Vector Autoregressive Model with the Multivariate Skew Normal Distribution for the Shocks: Application to Two Real-World Datasets [PDF]
فصلنامه پژوهشهای اقتصادی ایرانModeling plays a crucial role in economic and financial research, forming the foundation for analysis, decision-making, policy development, and planning.
Manijeh Mahmoodi +1 more
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Forecasting Value-at-Risk under Different Distributional Assumptions
Econometrics, 2016 Financial asset returns are known to be conditionally heteroskedastic and generally non-normally distributed, fat-tailed and often skewed. These features must be taken into account to produce accurate forecasts of Value-at-Risk (VaR).
Manuela Braione, Nicolas K. Scholtes
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Applied Multivariate Research, v.12 no.2 (complete version)
, 2006 The journal Applied Multivariate Research is sponsored by the Society for Applied Multivariate Research and specializes in publishing methodological and content papers that deal with the application of both classical and more modem multivariate ...
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BMC Medical Imaging, 2022 Background To assess the value of whole-lesion apparent diffusion coefficient (ADC) histogram analysis in differentiating stage IA endometrial carcinoma (EC) from benign endometrial lesions (BELs) and characterizing histopathologic features of stage IA ...
Jieying Zhang +7 more
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On Describing Multivariate Skewness: A Directional Approach [PDF]
Most multivariate measures of skewness in the literature measure the overall skewness of a distribution. While these measures are perfectly adequate for testing the hypothesis of distributional symmetry, their relevance for describing skewed ...
J. T. A. S. Ferreira, M. F. J. Steel
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