Power Estimation in Multivariate Analysis of Variance [PDF]
Tutorials in Quantitative Methods for Psychology, 2007 Power is often overlooked in designing multivariate studies for the simple reason that it is believed to be too complicated. In this paper, it is shown that power estimation in multivariate analysis of variance (MANOVA) can be approximated using a F ...
Jean François Allaire, Sylvain Chartier
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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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ks: Kernel Density Estimation and Kernel Discriminant Analysis for Multivariate Data in R [PDF]
Journal of Statistical Software, 2007 Kernel smoothing is one of the most widely used non-parametric data smoothing techniques. We introduce a new R package ks for multivariate kernel smoothing.
Tarn Duong
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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 analysis of curvature estimators [PDF]
Computer-Aided Design and Applications, 2016 ABSTRACTPrincipal curvature is one of the defining features of surfaces studied in differential geometry. While well-defined and easy to evaluate for smooth surfaces, it cannot be evaluated exactly if the surface is represented by a polygon mesh, unless some special conditions apply. Nevertheless, estimating the curvature of a surface mesh is a crucial
Libor Váša +2 more
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Performance analysis of multivariate complex amplitude estimators [PDF]
IEEE Transactions on Signal Processing, 2005 We consider multivariate complex amplitude estimation in the presence of unknown interference and noise. Two multivariate approaches [Maximum Likelihood (ML) and Capon] are provided. We derive the closed-form expression of the Crame/spl acute/r-Rao bound (CRB) for the unknown complex amplitudes.
Luzhou Xu, Jian Li 0001
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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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