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Multi-Platform Multivariate Regression with Group Sparsity for High-Dimensional Data Integration [PDF]
EntropyHigh-dimensional regression with multivariate responses poses significant challenges when data are collected across multiple platforms, each with potentially correlated outcomes.
Shanshan Qin +3 more
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Optimizing Forest Aboveground Biomass Models with Multi-Parameter Integration [PDF]
SensorsForests constitute a fundamental component of terrestrial carbon stocks and play a pivotal role in mitigating climate change through carbon sequestration.
Xinyi Liu, Yang Zhao
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Risk management via contemporaneous and temporal dependence structures with applications
MethodsX, 2021 This paper presents the estimation methods of the Bayesian Graphical Vector Auto-regression with and without innovations such as external regressors (BG-VAR(X)) and Bayesian Graphical Systems Equation Modelling with and without exogenous variables (BG ...
Emmanuel Senyo Fianu +2 more
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Multivariate Meta-Analysis of Genetic Association Studies: A Simulation Study. [PDF]
PLoS ONE, 2015 In a meta-analysis with multiple end points of interests that are correlated between or within studies, multivariate approach to meta-analysis has a potential to produce more precise estimates of effects by exploiting the correlation structure between ...
Binod Neupane, Joseph Beyene
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Estimation of a Matrix of Heterogeneity Parameters in Multivariate Meta-Analysis of Random-Effects Models [PDF]
Journal of Statistical Theory and Applications (JSTA), 2014 Multivariate meta-analysis has potential over its univariate counterpart. The most common challenge in univariate or multivariate meta-analysis is estimating heterogeneity parameters in non-negative domains under the random-effects model assumption.
Abera Wouhib
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Inclusion of Dominance Effects in the Multivariate GBLUP Model. [PDF]
PLoS ONE, 2016 New proposals for models and applications of prediction processes with data on molecular markers may help reduce the financial costs of and identify superior genotypes in maize breeding programs. Studies evaluating Genomic Best Linear Unbiased Prediction
Jhonathan Pedroso Rigal dos Santos +4 more
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Mathematics, 2022 The estimation of the covariance matrix is an important topic in the field of multivariate statistical analysis. In this paper, we propose a new estimator, which is a convex combination of the linear shrinkage estimation and the rotation-invariant ...
Yan Zhang +3 more
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Mathematics, 2022 Efficiency mapping has an important place in examining the maximum efficiency distribution as well as the energy consumption of designed electric motors at maximum torque and speed.
Oğuz Mısır, Mehmet Akar
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Latent Class Regression Utilizing Fuzzy Clusterwise Generalized Structured Component Analysis
Mathematics, 2020 Latent class analysis (LCA) has been applied in many research areas to disentangle the heterogeneity of a population. Despite its popularity, its estimation method is limited to maximum likelihood estimation (MLE), which requires large samples to satisfy
Seohee Park, Seongeun Kim, Ji Hoon Ryoo
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Efficient Density Estimation for High-Dimensional Data
IEEE Access, 2022 Multivariate density estimation methods typically work well in low dimensions and their extension to data analytics in high dimensions domain has proven challenging. For density estimation in high-dimensional big data domains, the non-parametric Bayesian
Aref Majdara, Saeid Nooshabadi
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