Results 1 to 10 of about 192,869 (306)
Nonlinear Shrinkage Estimation of Large-Dimensional Covariance Matrices [PDF]
The Annals of Statistics, 2011 Many statistical applications require an estimate of a covariance matrix and/or its inverse. When the matrix dimension is large compared to the sample size, which happens frequently, the sample covariance matrix is known to perform poorly and may suffer ...
Olivier Ledoit, Michael S. Wolf
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Group Lasso estimation of high-dimensional covariance matrices [PDF]
Journal of Machine Learning Research, 2010 In this paper, we consider the Group Lasso estimator of the covariance matrix of a stochastic process corrupted by an additive noise. We propose to estimate the covariance matrix in a high-dimensional setting under the assumption that the process has a ...
Jérémie Bigot +3 more
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Bounds for Estimation of Covariance Matrices From Heterogeneous Samples [PDF]
IEEE Transactions on Signal Processing, 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.
Olivier Besson +2 more
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Pose estimation by extended Kalman filter using noise covariance matrices based on sensor output [PDF]
ROBOMECH Journal, 2020 This paper presents an extended Kalman filter for pose estimation using noise covariance matrices based on sensor output. Compact and lightweight nine-axis motion sensors are used for motion analysis in widely various fields such as medical welfare and ...
Ayuko Saito +3 more
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Performance of penalized maximum likelihood in estimation of genetic covariances matrices [PDF]
Genetics Selection Evolution, 2011 Background Estimation of genetic covariance matrices for multivariate problems comprising more than a few traits is inherently problematic, since sampling variation increases dramatically with the number of traits. This paper investigates the efficacy of
Meyer Karin
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Remote Sensing, 2022 Precise and rapid extraction of spherical target features from laser point clouds is critical for achieving high-precision registration of multiple point clouds.
Ronghua Yang +3 more
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Distributed Fusion Filter for Nonlinear Multi-Sensor Systems With Correlated Noises
IEEE Access, 2020 This paper is concerned with distributed fusion (DF) estimation problem for nonlinear multi-sensor systems with correlated noises. Based on a recursive linear minimum variance estimation (RLMVE) framework, a novel filter is developed.
Gang Hao, Shuli Sun
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A finite-difference method for linearization in nonlinear estimation algorithms [PDF]
Modeling, Identification and Control, 1998 Linearizations of nonlinear functions that are based on Jacobian matrices often cannot be applied in practical applications of nonlinear estimation techniques. An alternative linearization method is presented in this paper.
Tor S. Schei
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Axioms, 2023 The generation of unprecedented amounts of data brings new challenges in data management, but also an opportunity to accelerate the identification of processes of multiple science disciplines.
Deniz Akdemir +2 more
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Estimation of Large-Dimensional Covariance Matrices via Second-Order Stein-Type Regularization
Entropy, 2022 This paper tackles the problem of estimating the covariance matrix in large-dimension and small-sample-size scenarios. Inspired by the well-known linear shrinkage estimation, we propose a novel second-order Stein-type regularization strategy to generate ...
Bin Zhang, Hengzhen Huang, Jianbin Chen
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