Assimilation of surface soil moisture into a multilayer soil model: design and evaluation at local scale by M. Parrens, J.-F. Mahfouf, A. L. Barbu, J.-C. Calvet

“…The introduction of vertical correlations in the background error covariance matrix is also encouraging. Using a yearly cumulative distribution function (CDF)-matching scheme for bias correction instead of matching over the three years permits the seasonal variability of the soil moisture content to be better transcribed. …”
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Improved One-Class Modeling of High-Dimensional Metabolomics Data via Eigenvalue-Shrinkage by Alberto Brini, Vahe Avagyan, Ric C. H. de Vos, Jack H. Vossen, Edwin R. van den Heuvel, Jasper Engel

“…They are based on a combination of the <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>MD</mi></mrow></semantics></math></inline-formula> and five so-called eigenvalue-shrinkage estimators of the covariance matrix of the reference class. A simple cross-validation procedure is proposed to set the critical limit for outlier detection. …”
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mbend: an R package for bending non-positive-definite symmetric matrices to positive-definite by Mohammad Ali Nilforooshan

“…Results Different bending procedures were conducted on a 5 × 5 covariance matrix (V), V converted to a correlation matrix (C) and an ill-conditioned 1000 × 1000 genomic relationship matrix (G). …”
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Structure of the transport uncertainty in mesoscale inversions of CO₂ sources and sinks using ensemble model simulations by J. Noilhan, P. Ciais, F. Chevallier, C. Sarrat, O. Pannekoucke, T. Lauvaux, P. J. Rayner

“…Finally, we compute the diagonal and non-diagonal terms of the observation error covariance matrix and introduced it into our CO₂ flux matrix inversion for 18 days of the 2005 intensive campaign CERES over the South West of France. …”
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Dryland Crop Classification Combining Multitype Features and Multitemporal Quad-Polarimetric RADARSAT-2 Imagery in Hebei Plain, China by Di Wang, Chang-An Liu, Yan Zeng, Tian Tian, Zheng Sun

“…Three quad-polarimetric RADARSAT-2 scenes were acquired between July and September 2018, from which 117 features were extracted using the Cloude–Pottier, Freeman–Durden, Yamaguchi, and multiple-component polarization decomposition methods, together with two polarization matrices (i.e., the coherency matrix and the covariance matrix). Random forest (RF) and support vector machine (SVM) algorithms were used for classification of dryland crops and other land-cover types in this study. …”
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A haplotype of polymorphisms in <it>ASE-1</it>, <it>RAI </it>and <it>ERCC1 </it>and the effects of tobacco smoking and alcohol consumption on risk of colorectal cancer: a danish pr... by Wallin Håkan, Overvad Kim, Tjønneland Anne, Sørensen Mette, Hansen Rikke D, Raaschou-Nielsen Ole, Vogel Ulla

“…Incidence rate ratio (IRR) were estimated by the Cox proportional hazards model stratified according to gender, and two-sided 95% confidence intervals (CI) and p-values were calculated based on robust estimates of the variance-covariance matrix and Wald's test of the Cox regression parameter.…”
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Floral signals evolve in a predictable way under artificial and pollinator selection in Brassica rapa by Zu, Pengjuan, Schiestl, Florian P., Gervasi, Daniel, Li, Xin, Runcie, Daniel, Guillaume, Frédéric

“…Using the observed selection gradients and the genetic variance-covariance matrix (G-matrix) of the traits, we showed that the observed responses of most floral traits including volatiles were predicted in the right direction in both artificial- and bumblebee-selection experiment. …”
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Data Fusion for Improved Respiration Rate Estimation by Nemati, Shamim, Malhotra, Atul, Clifford, Gari D.

“…A novel index of the underlying signal quality of respiratory signals is presented and then used to modify the noise covariance matrix of the KF which discounts the effect of noisy data. …”
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On Space–Frequency Correlation of UWB MIMO Channels by Hong, Xuemin, Wang, Cheng-Xiang, Thompson, John, Allen, Ben, Ge, Xiaohu, Malik, Wasim Qamar

“…We demonstrate that, compared with a conventional model that only considers amplitude correlation, a UWB MIMO channel model taking into account both amplitude and ToA correlations leads to different theoretical maximum diversity order, numerical structure of the SF channel covariance matrix, spatial correlation function, and diversity performance. …”
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Krylov subspace estimation by Schneider, Michael K. (Michael Klaus)

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Internal multiscale autoregressive processes, stochastic realization, and covariance extension by Frakt, Austin B. (Austin Berk)

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Learning Gaussian Graphical Models with Observed or Latent FVSs by Liu, Ying, Willsky, Alan S.

“…Regardless of the maximum degree, without knowing the full graph structure, we can exactly compute the maximum likelihood estimate with complexity O(kn[superscript 2] + n[superscript 2] log n) if the FVS is known or in polynomial time if the FVS is unknown but has bounded size. 2) The FVS nodes are latent variables, where structure learning is equivalent to decomposing an inverse covariance matrix (exactly or approximately) into the sum of a tree-structured matrix and a low-rank matrix. …”
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The gravity field, orientation, and ephemeris of Mercury from MESSENGER observations after three years in orbit by Mazarico, Erwan Matias, Genova, Antonio, Goossens, Sander, Lemoine, Frank G., Neumann, Gregory A., Solomon, Sean C., Zuber, Maria, Smith, David Edmund

“…We present a detailed analysis of the HgM005 covariance matrix, and we describe some near-circular frozen orbits around Mercury that could be advantageous for future exploration.…”
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Incremental rule splitting in generalized evolving fuzzy systems for autonomous drift compensation by Lughofer, Edwin, Pratama, Mahardhika, Skrjanc, Igor

“…The splitting technique relies on the eigendecomposition of the rule covariance matrix to adequately manipulate the largest eigenvector and eigenvalues in order to retrieve the new centers and contours of the two split rules. …”
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Bayesian operational modal analysis of structures with tuned mass damper by Wang, Xinrui, Zhu, Zuo, Au, Siu-Kui

“…Analytical expressions are derived so that the ‘posterior’ (i.e., given data) covariance matrix can be determined accurately and efficiently. …”
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Adaptive evolution strategies for stochastic zeroth-order optimization by He, Xiaoyu, Zheng, Zibin, Chen, Zefeng, Zhou, Yuren

“…Based on this framework, we implement a step-size adaptation rule and two covariance matrix adaptation rules, where the former can automatically tune the step-sizes and the latter are intended to cope with ill-conditioning. …”
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Distributed anomaly detection scheme based on lightweight data aggregation in wireless sensor network by Mohd. Zamry, Nurfazrina

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The 2dF Galaxy Redshift Survey: power-spectrum analysis of the final data set and cosmological implications by Cole, S, Percival, W, Peacock, J, Norberg, P, Baugh, C, Frenk, C, Baldry, I, Bland-Hawthorn, J, Bridges, T, Cannon, R, Colless, M, Collins, C, Couch, W, Cross, N, Dalton, G, Eke, V, De Propris, R, Driver, S, Efstathiou, G, Ellis, R, Glazebrook, K, Jackson, C, Jenkins, A, Lahav, O, Lewis, I

“…The redshift selection function is determined by dividing the survey according to rest-frame colour, and deducing a self-consistent treatment of k-corrections and evolution for each population. The covariance matrix for the power-spectrum estimates is determined using two different approaches to the construction of mock surveys, which are used to demonstrate that the input cosmological model can be correctly recovered. …”

Time-varying source reconstruction by Timms, R

“…To date, the majority of source localisation algorithms employ static approximations to the data covariance matrix.</p> <p>Here we make the argument that researchers should consider a Temporally Adaptive SourcE Reconstruction (TASER) approach to solving the inverse problem. …”

Comparison of the genetic algorithm and incremental optimisation routines for a Bayesian inverse modelling based network design by Nickless, A, Rayner, P, Erni, B, Scholes, R

“…The GA solution set showed more inconsistency if the number of iterations or population size was small, and more so for a complex prior flux covariance matrix. If the GA completed with a sub-optimal solution, these solutions were similar in fitness to the best available solution. …”