Results 31 to 40 of about 1,042,431 (269)
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
A Robust Statistics Approach to Minimum Variance Portfolio Optimization [PDF]
, 2015 We study the design of portfolios under a minimum risk criterion. The performance of the optimized portfolio relies on the accuracy of the estimated covariance matrix of the portfolio asset returns.
Couillet, Romain +2 more
core +4 more sources
Physical properties of the Schur complement of local covariance matrices [PDF]
, 2007 General properties of global covariance matrices representing bipartite Gaussian states can be decomposed into properties of local covariance matrices and their Schur complements. We demonstrate that given a bipartite Gaussian state $\rho_{12}$ described
Eisert J Wolf M M +7 more
core +2 more sources
Local Matrix Feature-Based Kernel Joint Sparse Representation for Hyperspectral Image Classification
Remote Sensing, 2022 Hyperspectral image (HSI) classification is one of the hot research topics in the field of remote sensing. The performance of HSI classification greatly depends on the effectiveness of feature learning or feature design. Traditional vector-based spectral–
Xiang Chen +3 more
doaj +1 more source
Covariance-on-covariance regression
BiometricsABSTRACT A covariance-on-covariance regression model is introduced in this manuscript. It is assumed that there exists (at least) a pair of linear projections on outcome covariance matrices and predictor covariance matrices such that a log-linear model links the variances in the projection spaces, as well as additional covariates of ...
Yi Zhao, Yize Zhao
openaire +2 more sources
Bispectrum Supersample Covariance
, 2018 Modes with wavelengths larger than the survey window can have significant impact on the covariance within the survey window. The supersample covariance has been recognized as an important source of covariance for the power spectrum on small scales, and ...
Chan, Kwan Chuen +2 more
core +1 more source
Shrinkage Estimation of the Power Spectrum Covariance Matrix [PDF]
, 2008 We seek to improve estimates of the power spectrum covariance matrix from a limited number of simulations by employing a novel statistical technique known as shrinkage estimation.
Adrian C. Pope +14 more
core +1 more source
, 2000 We introduce new definitions of states and of representations of covariance systems. The GNS-construction is generalized to this context. It associates a representation with each state of the covariance system.
Bargmann V +17 more
core +3 more sources
Optimal Estimation and Rank Detection for Sparse Spiked Covariance Matrices [PDF]
, 2015 This paper considers sparse spiked covariance matrix models in the high-dimensional setting and studies the minimax estimation of the covariance matrix and the principal subspace as well as the minimax rank detection.
Cai, Tony, Ma, Zongming, Wu, Yihong
core +3 more sources
The calibration of GPS receivers applying the calibration bases
Geodesy and Cartography, 2012 Till now there are no written standards and other legal documents for the calibration of GPS receivers. Self-calibration procedures are used for calibration of some types of instrument.
Jonas Skeivalas, Raimundas Putrimas
doaj +1 more source