Results 21 to 30 of about 910,963 (262)
Reaction Cross Section and Covariance Evaluation of 56Fe(n,p)56Mn below 35 MeV
Yuanzineng kexue jishu, 2022 Neutron induced reaction cross sections play an important role in nuclear science and technology research, such as national defense, nuclear energy construction and development, nuclear medicine, radiation protection and nuclear safety.
LI Xiaojun;LAN Changlin;ZHANG Yue;YANG XianlinZHANG Zhi;SUN Xiaodong
doaj
Bayesian Sparse Factor Analysis of Genetic Covariance Matrices [PDF]
, 2013 Quantitative genetic studies that model complex, multivariate phenotypes are important for both evolutionary prediction and artificial selection. For example, changes in gene expression can provide insight into developmental and physiological mechanisms ...
Mukherjee, Sayan, Runcie, Daniel E
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Factors affecting the performance of Pantaneiro horses
Revista Brasileira de Zootecnia, 2018 This study aimed to assess the physical performance of Pantaneiro horses with and without equine infectious anemia (EIA) under functional conditions of cattle management. The horses were subjected to a performance test and split into two groups according
Geraldo da Silva e Souza +7 more
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Efficient Estimation of Approximate Factor Models via Regularized Maximum Likelihood [PDF]
, 2012 We study the estimation of a high dimensional approximate factor model in the presence of both cross sectional dependence and heteroskedasticity. The classical method of principal components analysis (PCA) does not efficiently estimate the factor ...
Bai, Jushan, Liao, Yuan
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Sensors, 2017 Railway track irregularity surveying is important for the construction and the maintenance of railway lines. With the development of inertial devices, systems based on Inertial Navigation System (INS) have become feasible and popular approaches in track ...
Qingan Jiang +3 more
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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
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Estimating Mean and Covariance Structure with Reweighted Least Squares [PDF]
, 2020 Does Reweighted Least Squares (RLS) perform better in small samples than maximum likelihood (ML) for mean and covariance structure? ML statistics in covariance structure analysis are based on the asymptotic normality assumption; however, actual ...
Zheng, Bang Quan
core
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 +2 more
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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 +2 more
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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 +2 more
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