Results 31 to 40 of about 25,409,385 (300)

A Network-Based Analysis for Evaluating Conditional Covariance Estimates

Mathematics, 2023
The modeling and forecasting of dynamically varying covariances has received a great deal of attention in the literature. The two most widely used conditional covariances and correlations models are BEKK and the DCC.
Carlo Drago, Andrea Scozzari
doaj   +1 more source

Ajuste do rendimento para a variação do estande em experimentos de melhoramento genético do feijão Adjustment of the yield for the stand variation in common bean genetic breeding experiments

Pesquisa Agropecuária Brasileira, 2007
O objetivo deste trabalho foi avaliar o ajuste do rendimento pela variação do estande em experimentos de feijão e propor procedimento para ajustamento por análise de co-variação.
Clause Fátima de Brum Piana, João Gilberto Corrêa da Silva, Irajá Ferreira Antunes   +2 more
doaj   +1 more source

IPCO: Inference of Pathways from Co-variance analysis

BMC Bioinformatics, 2020
Background Key aspects of microbiome research are the accurate identification of taxa and the profiling of their functionality. Amplicon profiling based on the 16S ribosomal DNA sequence is a ubiquitous technique to identify and profile the abundance of ...
Mrinmoy Das, Tarini Shankar Ghosh, Ian B. Jeffery   +2 more
doaj   +1 more source

Pyrcca: regularized kernel canonical correlation analysis in Python and its applications to neuroimaging

Frontiers in Neuroinformatics, 2016
In this article we introduce Pyrcca, an open-source Python package for performing canonical correlation analysis (CCA). CCA is a multivariate analysis method for identifying relationships between sets of variables.
Natalia Y Bilenko, Jack L Gallant, Jack L Gallant   +2 more
doaj   +1 more source

Inferring single neuron properties in conductance-based balanced networks

Frontiers in Computational Neuroscience, 2011
Balanced states in large networks are a usual hypothesis for explaining the variability of neural activity in cortical systems. These states give rise to a generic behavior in which the individual dynamics of the neurons is almost irrelevant.
Germán eMato, Roman eRossi Pool
doaj   +1 more source

Covariance-enhanced discriminant analysis

Biometrika, 2014
Linear discriminant analysis has been widely used to characterize or separate multiple classes via linear combinations of features. However, the high dimensionality of features from modern biological experiments defies traditional discriminant analysis techniques.
Peirong Xu, Ji Zhu, Lixing Zhu, Yi Li
openaire   +4 more sources

A cautionary note on the use of the Analysis of Covariance (ANCOVA) in classification designs with and without within-subject factors

Frontiers in Psychology, 2015
A number of statistical textbooks recommend using an analysis of covariance (ANCOVA) to control for the effects of extraneous factors that might influence the dependent measure of interest. However, it is not generally recognized that serious problems of
Bruce A Schneider, Meital eAvivi-Reich, Mindaugas eMozuraitis   +2 more
doaj   +1 more source

Covariance Matrix Preparation for Quantum Principal Component Analysis

PRX Quantum, 2022
Principal component analysis (PCA) is a dimensionality reduction method in data analysis that involves diagonalizing the covariance matrix of the dataset.
Max Hunter Gordon, M. Cerezo, Lukasz Cincio, Patrick J. Coles   +3 more
doaj   +1 more source

Structural Covariance Network Disruption and Functional Compensation in Parkinson’s Disease

Frontiers in Aging Neuroscience, 2020
Purpose: To investigate the structural covariance network disruption in Parkinson’s disease (PD), and explore the functional alterations of disrupted structural covariance network.Methods: A cohort of 100 PD patients and 70 healthy participants underwent
Cheng Zhou, Ting Gao, Tao Guo, Jingjing Wu, Xiaojun Guan, Weiwen Zhou, Peiyu Huang, Min Xuan, Quanquan Gu, Xiaojun Xu, Shunren Xia, Dexing Kong, Jian Wu, Minming Zhang   +13 more
doaj   +1 more source

Real‐World Performance of CSF Kappa Free Light Chains in the 2024 McDonald Criteria

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Kappa free light chains (KFLCs) in the cerebrospinal fluid (CSF) have a similar performance to CSF‐restricted oligoclonal bands (OCB) for multiple sclerosis (MS) diagnosis. To help with implementation, we set out to resolve several remaining uncertainties: (1) performance in a real‐world cohort and the 2024 McDonald criteria; (2 ...
Maya M. Leibowitz, Ryan Cooper, Stefania Kaninia, Kathryn I. Challis, Will Greenway, Maria Bonello, Mahmoud Elbahnasawi, Deborah T. Shode, Dominika Gajdasik, Victor Iliev, Alison M. E. Whitelegg, Ian Galea   +11 more
wiley   +1 more source