Results 11 to 20 of about 1,082,135 (333)
Law of Log Determinant of Sample Covariance Matrix and Optimal Estimation of Differential Entropy for High-Dimensional Gaussian Distributions [PDF]
, 2013 Differential entropy and log determinant of the covariance matrix of a multivariate Gaussian distribution have many applications in coding, communications, signal processing and statistical inference.
Cai, T. Tony +2 more
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Covariance of Covariance Features for Image Classification [PDF]
Proceedings of International Conference on Multimedia Retrieval, 2014 In this paper we propose a novel image descriptor built by computing the covariance of pixel level features on densely sampled patches and encoding them using their covariance. Appropriate projections to the Euclidean space and feature normalizations are employed in order to provide a strong descriptor usable with linear classifiers. In order to remove
SERRA, GIUSEPPE +3 more
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Covariate Order Tests for Covariate Effect [PDF]
Lifetime Data Analysis, 2002 A new approach for constructing tests for association between a random right censored life time variable and a covariate is proposed. The basic idea is to first arrange the observations in increasing order of the covariate and then base the test on a certain point process defined by the observation times.
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Brownian distance covariance [PDF]
, 2010 Distance correlation is a new class of multivariate dependence coefficients applicable to random vectors of arbitrary and not necessarily equal dimension.
J. Székely, L. Rizzo, Maria
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Estimating the power spectrum covariance matrix with fewer mock samples [PDF]
, 2015 The covariance matrices of power-spectrum (P(k)) measurements from galaxy surveys are difficult to compute theoretically. The current best practice is to estimate covariance matrices by computing a sample covariance of a large number of mock catalogues ...
Pearson, David W., Samushia, Lado
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Covariance Estimation in High Dimensions via Kronecker Product Expansions [PDF]
, 2013 This paper presents a new method for estimating high dimensional covariance matrices. The method, permuted rank-penalized least-squares (PRLS), is based on a Kronecker product series expansion of the true covariance matrix. Assuming an i.i.d.
Alfred O. Hero Iii +2 more
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Pesquisa Agropecuária Brasileira, 2009 O objetivo deste trabalho foi estudar diferentes covariáveis de competição em análises de vizinhança, e verificar sua eficiência no aumento da precisão experimental e as consequências no ordenamento de genótipos de cana-de-açúcar em termos de potencial ...
Liliam Silvia Candido +3 more
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Covariate Assisted Principal Regression for Covariance Matrix Outcomes [PDF]
Biostatistics, 2018 AbstractModeling variances in data has been an important topic in many fields, including in financial and neuroimaging analysis. We consider the problem of regressing covariance matrices on a vector covariates, collected from each observational unit. The main aim is to uncover the variation in the covariance matrices across units that are explained by ...
Zhao, Yi +4 more
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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
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Finitely additive functions in measure theory and applications [PDF]
Opuscula MathematicaIn this paper, we consider, and make precise, a certain extension of the Radon-Nikodym derivative operator, to functions which are additive, but not necessarily sigma-additive, on a subset of a given sigma-algebra.
Daniel Alpay, Palle Jorgensen
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