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Patterns of phenotypic covariation and correlation in modern humans as viewed from morphological integration
(Wiley-liss, Div John Wiley & Sons Inc, 2003-05)
Proportionality of phenotypic and genetic distance is of crucial importance to adequately focus on population history and structure, and depends on proportionality of genetic and phenotypic covariance. Constancy of phenotypic ...
Covariance reducing models: An alternative to spectral modelling of covariance matrices
(Oxford University Press, 2008-12)
We introduce covariance reducing models for studying the sample covariance matrices of a random vector observed in different populations. The models are based on reducing the sample covariance matrices to an informational ...
Signal detection in high dimension: the multispiked case
(Inst Mathematical Statistics, 2014-02)
This paper applies Le Cam's asymptotic theory of statistical experiments to the signal detection problem in high dimension. We consider the problem of testing the null hypothesis of sphericity of a high-dimensional covariance ...
Forecasting large covariance matrices: comparing autometrics and LASSOVAR
(2019)
This study aims to compare the performance of two well known automatic model selection algorithms, Autometrics (Hendry and Krolzig, 1999; Doornik, 2009), LASSOVAR and adaptive LASSOVAR (Callot et al., 2017) for modelling ...
Assessing the estimation of nearly singular covariance matrices for modeling spatial variables
(Wiley, 2023)
© 2023, Institute of Mathematical Statistics. All rights reserved.Spatial analysis commonly relies on the estimation of a co-variance matrix associated with a random field. This estimation strongly impacts the prediction ...
Analysis on the Empirical Spectral Distribution of Large Sample Covariance Matrix and Applications for Large Antenna Array Processing
(Institute of Electrical and Electronics Engineers Inc., 2019)
This paper addresses the asymptotic behavior of a particular type of information-plus-noise-type matrices, where the column and row numbers of the matrices are large and of the same order, while signals have diverged and ...
Measurement error models with nonconstant covariance matrices
(ACADEMIC PRESS, 2002)
Measurement error models with nonconstant covariance matrices
(ACADEMIC PRESS INC ELSEVIER SCIENCE, 2002)
In this paper we consider measurement error models when the observed random vectors are independent and have mean vector and covariance matrix changing with each observation. The asymptotic behavior of the sample mean ...