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The Minimum Regularized Covariance Determinant Estimator [PDF]
SSRN Electronic Journal, 2017 The Minimum Covariance Determinant (MCD) approach robustly estimates the location and scatter matrix using the subset of given size with lowest sample covariance determinant. Its main drawback is that it cannot be applied when the dimension exceeds the subset size. We propose the Minimum Regularized Covariance Determinant (MRCD) approach, which differs
Boudt, Kris +3 more
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Covariance matrix estimation with heterogeneous samples [PDF]
, 2008 We consider the problem of estimating the covariance matrix Mp of an observation vector, using heterogeneous training samples, i.e., samples whose covariance matrices are not exactly Mp.
Besson, Olivier +2 more
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Combining Partially Overlapping Multi-Omics Data in Databases Using Relationship Matrices
Frontiers in Plant Science, 2020 Private and public breeding programs, as well as companies and universities, have developed different genomics technologies that have resulted in the generation of unprecedented amounts of sequence data, which bring new challenges in terms of data ...
Deniz Akdemir +3 more
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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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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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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 popularto 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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Bounds for estimation of covariance matrices from heterogeneous samples [PDF]
, 2008 This correspondence derives lower bounds on the mean-square error (MSE) for the estimation of a covariance matrix mbi Mp, using samples mbi Zk,k=1,...,K, whose covariance matrices mbi Mk are randomly distributed around mbi Mp.
Besson, Olivier +2 more
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Best linear unbiased estimation for varying probability with and without replacement sampling
Special Matrices, 2019 When sample survey data with complex design (stratification, clustering, unequal selection or inclusion probabilities, and weighting) are used for linear models, estimation of model parameters and their covariance matrices becomes complicated.
Haslett Stephen
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Channel Covariance Identification in FDD Massive MIMO Systems
Proceedings, 2018 Channel estimation for Massive MIMO systems has drawn a lot of attention in the last years. A number of estimation methods rely on the knowledge of the channel covariance matrix to operate. However, this covariance is not known in practice, and it should
José P. González-Coma +3 more
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