Directional variance adjustment: bias reduction in covariance matrices based on factor analysis with an application to portfolio optimization. [PDF]
Robust and reliable covariance estimates play a decisive role in financial and many other applications. An important class of estimators is based on factor models.
Daniel Bartz +4 more
doaj +1 more source
Convex Banding of the Covariance Matrix [PDF]
We introduce a new sparse estimator of the covariance matrix for high-dimensional models in which the variables have a known ordering. Our estimator, which is the solution to a convex optimization problem, is equivalently expressed as an estimator which ...
Bien, Jacob +2 more
core +2 more sources
Random matrix-improved estimation of covariance matrix distances [PDF]
Given two sets $x_1^{(1)},\ldots,x_{n_1}^{(1)}$ and $x_1^{(2)},\ldots,x_{n_2}^{(2)}\in\mathbb{R}^p$ (or $\mathbb{C}^p$) of random vectors with zero mean and positive definite covariance matrices $C_1$ and $C_2\in\mathbb{R}^{p\times p}$ (or $\mathbb{C}^{p\times p}$), respectively, this article provides novel estimators for a wide range of distances ...
Couillet, Romain +3 more
openaire +3 more sources
Accelerated Discovery of High Performance Ni3S4/Ni3Mo HER Catalysts via Bayesian Optimization
Integrated workflow accelerates the catalyst discovery of hydrogen evolution reaction via Bayesian optimization. An experiment‐trained surrogate model proposes synthesis conditions, guiding iterative refinement using electrochemical performance metrics.
Namuersaihan Namuersaihan +9 more
wiley +1 more source
Positive definite estimation of large covariance matrix using generalized nonconvex penalties
This paper addresses the issue of large covariance matrix estimation in a high-dimensional statistical analysis. Recently, improved iterative algorithms with positive-definite guarantee have been developed.
Fei Wen +3 more
doaj +1 more source
We present a fully automated Bayesian optimization (BO) protocol for the parameterization of nonbonded interactions in coarse‐grain CG force fields (BACH). Using experimental thermophysical data, we apply the protocol to a broad range of liquids, spanning linear, branched, and unsaturated hydrocarbons, esters, triglycerides, and water.
Janak Prabhu +3 more
wiley +1 more source
Relative Efficiency of Maximum Likelihood and Other Estimators in a Nonlinear Regression Model with Small Measurement Errors [PDF]
We compare the asymptotic covariance matrix of the ML estimator in a nonlinear measurement error model to the asymptotic covariance matrices of the CS and SQS estimators studied in Kukush et al (2002). For small measurement error variances they are equal
Kukush, Alexander, Schneeweiß, Hans
core +2 more sources
A large number of MoS2 flakes were screened to obtain high‐quality flakes based on optical intensities in R, G, and B channel images. The flakes were classified from Level 1 to 6 based on optical intensities in the R, G, and B channel images. Low‐quality flake exhibited wrinkled, folded, or overlapped features, while high‐quality displayed a neat ...
Sanghyun Lee +11 more
wiley +1 more source
Assessment of Covariance Selection Methods in High-Dimensional Gaussian Graphical Models
The covariance selection in Gaussian graphical models consists in selecting, based on a sample of a multivariate normal vector, all those pairs of variables that are conditionally dependent given the remaining variables.
J. Maldonado, S. M. Ruiz
doaj +1 more source
A Synovium‐on‐Chip Platform to Study Multicellular Interactions in Arthritis
The Synovium‐on‐Chip comprises a thin microporous PDMS membrane to support co‐culture of fibroblast‐like synoviocytes (FLS), THP‐1‐derived macrophages, and endothelial cells, enabling real‐time analysis of synovial‐vascular interactions. FLS migration through the pores drives endothelial remodeling, while TNF‐α stimulation induces robust inflammatory ...
Laurens R. Spoelstra +8 more
wiley +1 more source

