Results 41 to 50 of about 115,259 (238)

On describing multivariate skewed distributions: A directional approach [PDF]

Canadian Journal of Statistics, 2006
AbstractMost multivariate measures of skewness in the literature measure the overall skewness of a distribution. These measures were designed for testing the hypothesis of distributional symmetry; their relevance for describing skewed distributions is less obvious.
Ferreira, José T. A. S., Steel, Mark F. J.   +1 more
openaire   +2 more sources

Deep Learning‐Assisted Coherent Raman Scattering Microscopy

Advanced Intelligent Discovery, EarlyView.
The analytical capabilities of coherent Raman scattering microscopy are augmented through deep learning integration. This synergistic paradigm improves fundamental performance via denoising, deconvolution, and hyperspectral unmixing. Concurrently, it enhances downstream image analysis including subcellular localization, virtual staining, and clinical ...
Jianlin Liu, Rujia Liu, Xinyan Zhang, Xun Chen, Shuhua Yue   +4 more
wiley   +1 more source

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, Kaleb L. Leemaqz, Geoffrey J. McLachlan   +2 more
openaire   +5 more sources

Explaining the Origin of Negative Poisson's Ratio in Amorphous Networks With Machine Learning

Advanced Intelligent Discovery, EarlyView.
This review summarizes how machine learning (ML) breaks the “vicious cycle” in designing auxetic amorphous networks. By transitioning from traditional “black‐box” optimization to an interpretable “AI‐Physics” closed‐loop paradigm, ML is shown to not only discover highly optimized structures—such as all‐convex polygon networks—but also unveil hidden ...
Shengyu Lu, Xiangying Shen
wiley   +1 more source

An Autonomous Large Language Model‐Agent Framework for Transparent and Local Time Series Forecasting

Advanced Intelligent Discovery, EarlyView.
Architecture of the proposed large language model (LLM)‐based agent framework for autonomous time series forecasting in thermal power generation systems. The framework operates through a vertical pipeline initiated by natural language queries from users, which are processed by the LLM Agent Core powered by Llama.cpp and a ReAct loop with persistent ...
William Gouvêa Buratto, Gabriel Villarrubia Gonzalez, Ademir Nied, Laio Oriel Seman, Anne Carolina Rodrigues Klaar, Stefano Frizzo Stefenon   +5 more
wiley   +1 more source

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
core  

Electrocardiographic and Skin Manifestations of Turner Syndrome: Association With Cardiovascular Disease

American Journal of Medical Genetics Part A, EarlyView.
ABSTRACT Congenital heart disease (CHD) and dermatologic conditions such as lymphedema and acquired melanocytic nevi (AMN) are common in Turner Syndrome (TS). We hypothesized that abnormalities of cranial neural crest cell derivatives drive the skin and heart manifestations of TS. We conducted joint cardiac and skin examinations of volunteers at a 2023
Sarah Elsaim, Brett Vernier, Van Thi Thanh Truong, Riya T. Patel, Matthew Brown, Martin Chacon Portillo, Megan Rogge, David Rodriguez‐Buritica, Siddharth K. Prakash   +8 more
wiley   +1 more source

MaxSkew and MultiSkew: Two R Packages for Detecting, Measuring and Removing Multivariate Skewness

, 2019
Skewness plays a relevant role in several multivariate statistical techniques. Sometimes it is used to recover data features, as in cluster analysis. In other circumstances, skewness impairs the performances of statistical methods, as in the Hotelling's ...
Franceschini, Cinzia, Loperfido, Nicola
core  

A General Class of Multivariate Skew-Elliptical Distributions

Journal of Multivariate Analysis, 2001
Let \({\mathbf X}= (X_1,\dots, X_k)^T\) be a random vector elliptically distributed with location vector \(\mu\in \mathbb{R}^k\) and \(k\times k\) (positive definite) dispersion matrix \(\Sigma\), and assume that the vector \((X_0, X_1,\dots, X_k)^T\) is also elliptically distributed with location vector \((0,\mu)\) and dispersion matrix \(\left ...
Branco, Márcia D., Dey, Dipak K.
openaire   +2 more sources

CSF‐Compartmentalized Antibody Glycoprofiles in NMDAR Encephalitis Associate with Etiology and Functional Recovery

Annals of Neurology, EarlyView.
Objective To characterize Fc‐glycosylation profiles in patients with anti‐N‐methyl‐D‐aspartate receptor encephalitis (NMDARe) and assess their association with antibody compartmentalization (cerebrospinal fluid [CSF] vs serum), disease triggers (viral, tumor‐related or idiopathic), and 1‐year outcomes.
Laura Marmolejo, Claudia Papi, Chiara Milano, Esther Aguilar, Estibaliz Maudes, Ivana Duvnjak Orešković, Jerko Štambuk, Maja Pučić‐Baković, Gemma Olivé‐Cirera, Elianet Fonseca, Mar Guasp, Eugenia Martinez‐Hernandez, Helena Ariño, Takahiro Iizuka, Thais Armangué, Josep Dalmau, Marianna Spatola   +16 more
wiley   +1 more source