Results 41 to 50 of about 1,787,003 (299)
Covariance matrix estimation methods for constrained portfolio optimization in a South African setting [PDF]
, 2010 One of the major topics of concern in Modern Portfolio Theory is portfolio optimization which is centred on the mean-variance framework. In order for this framework to be implemented, esti- mated parameters (covariance matrix for the constrained portfo ...
Madume, Jaison Pezisai
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Estimating Covariance Matrices
The Annals of Statistics, 1991 Let \(S_ 1\sim W_ p(\Sigma_ 1,n_ 1)\) and \(S_ 2\sim W_ p(\Sigma_ 2,n_ 2)\) be two independent \(p\times p\) Wishart matrices. It is desired to consider the minimax estimation of \((\Sigma_ 1,\Sigma_ 2)\) under the loss function \[ \sum_{i=1}^ 2\{\hbox {tr}(\Sigma_ i^{-1}\hat\Sigma_ i-\log| \Sigma_ i^{- 1}\hat\Sigma_ i|-p\}, \] extending known results ...
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On the maximum of covariance estimators
Journal of Multivariate Analysis, 2011 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Applied Sciences, 2022 A covariance matrix is an important parameter in many computational applications, such as quantitative trading. Recently, a global minimum variance portfolio received great attention due to its performance after the 2007–2008 financial crisis, and this ...
Tuan Tran, Nhat Nguyen, Trung Nguyen
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On the Nonparametric Estimation of Covariance Functions
The Annals of Statistics, 1994 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Hall, Peter +2 more
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Geodesic Convexity and Covariance Estimation [PDF]
IEEE Transactions on Signal Processing, 2012 Geodesic convexity is a generalization of classical convexity which guarantees that all local minima of g-convex functions are globally optimal. We consider g-convex functions with positive definite matrix variables, and prove that Kronecker products, and logarithms of determinants are g-convex.
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Evaluation of structure specification in linear mixed models for modeling the spatial effects in tree height-diamater relationships [PDF]
Annals of Forest Research, 2013 In recent years, linear mixed models (LMM) have become more popular to deal with spatial effects in forestry and ecological data. In this study, different structure specifications of linear mixed model were applied to model tree height-diameter ...
Junfeng Lu, Lianjun Zhang
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Study of harmonics detection based on parametric spectral estimation method
Gong-kuang zidonghua, 2016 Three parametric spectral estimation methods including Yule Walker, Burg and Covariance were studied and an improved Covariance method was proposed based on analysis of AR model.
ZHANG Tingzhong +3 more
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Estimating cosmological parameter covariance [PDF]
Monthly Notices of the Royal Astronomical Society, 2014 We investigate the bias and error in estimates of the cosmological parameter covariance matrix, due to sampling or modelling the data covariance matrix, for likelihood width and peak scatter estimators. We show that these estimators do not coincide unless the data covariance is exactly known. For sampled data covariances, with Gaussian distributed data
Taylor, Andy, Joachimi, Benjamin
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Molecular Oncology, EarlyView.This study integrates publicly available transcriptomic datasets to identify molecular signatures associated with response to neoadjuvant chemoradiotherapy in locally advanced rectal cancer. By analyzing a combination of multiple cohorts with bioinformatics approaches, we reveal biological pathways and immune‐related features that may improve ...
Aleksandra Stanojevic +10 more
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