Results 31 to 40 of about 556,837 (257)

A Robust Adaptive Unscented Kalman Filter for Nonlinear Estimation with Uncertain Noise Covariance

Sensors, 2018
The Unscented Kalman filter (UKF) may suffer from performance degradation and even divergence while mismatch between the noise distribution assumed as a priori by users and the actual ones in a real nonlinear system.
Binqi Zheng, Pengcheng Fu, Baoqing Li, Xiaobing Yuan   +3 more
doaj   +1 more source

Estimating Covariance Matrices

The Annals of Statistics, 1991
Let \(S_ 1\sim W_ p(\Sigma_ 1,n_ 1)\) and \(S_ 2\sim W_ p(\Sigma_ 2,n_ 2)\) be two independent \(p\times p\) Wishart matrices. It is desired to consider the minimax estimation of \((\Sigma_ 1,\Sigma_ 2)\) under the loss function \[ \sum_{i=1}^ 2\{\hbox {tr}(\Sigma_ i^{-1}\hat\Sigma_ i-\log| \Sigma_ i^{- 1}\hat\Sigma_ i|-p\}, \] extending known results ...
openaire   +2 more sources

Covariance matrices and valuations

Advances in Applied Mathematics, 2013
The moment matrix of a function \(f\) of real variables \(x_1,\dots,x_n\) is the matrix, whose \((i,j)\)-th entry is the integral of \(x_i x_j f\) over \(\mathbb{R}^n\). The moment matrix can be regarded as a matrix-valued valuation on the space of functions with finite second moments: recall that a valuation on a space of functions \(L\) is a function
openaire   +1 more source

bspcov: An R Package for Bayesian sparse covariance matrix estimation

SoftwareX
The bspcov R package provides a Bayesian inference for covariance matrices. The bspcov is developed to aid in research that involves estimating constrained covariance matrices by enabling the use of state-of-the-art Bayesian inference methods.
Kyeongwon Lee, Kyoungjae Lee, Seongil Jo, Kwangmin Lee   +3 more
doaj   +1 more source

Spiked sample covariance matrices with possibly multiple bulk components

, 2020
In this paper, we study the convergent limits and rates of the eigenvalues and eigenvectors for spiked sample covariance matrices whose spectrum can have multiple bulk components.
Ding, Xiucai, Xiucai Ding
core   +1 more source

Limiting Spectral Distribution of Large-Dimensional Sample Covariance Matrices Generated by the Periodic Autoregressive Model

Journal of Mathematics, 2021
The explicit representation for the limiting spectral moments of sample covariance matrices generated by the periodic autoregressive model (PAR) is established.
Jin Zou, Dong Han
doaj   +1 more source

Do unbalanced data have a negative effect on LDA? [PDF]

, 2008
For two-class discrimination, Xie and Qiu [The effect of imbalanced data sets on LDA: a theoretical and empirical analysis, Pattern Recognition 40 (2) (2007) 557–562] claimed that, when covariance matrices of the two classes were unequal, a (class ...
Titterington, D.M., Xue, J.H.
core   +1 more source

Profiling neoadjuvant therapy response in rectal cancer using meta‐analysis of publicly available transcriptomic RNA‐seq datasets

Molecular Oncology, EarlyView.
This study integrates publicly available transcriptomic datasets to identify molecular signatures associated with response to neoadjuvant chemoradiotherapy in locally advanced rectal cancer. By analyzing a combination of multiple cohorts with bioinformatics approaches, we reveal biological pathways and immune‐related features that may improve ...
Aleksandra Stanojevic, Rafael Stroggilos, Mladen Marinkovic, Ana Djuric, Suzana Stojanovic‐Rundic, Radmila Jankovic, Sergi Castellvi‐Bel, Remond J.A. Fijneman, Antonia Vlahou, Jerome Zoidakis, Milena Cavic   +10 more
wiley   +1 more source

HLIBCov: Parallel hierarchical matrix approximation of large covariance matrices and likelihoods with applications in parameter identification

MethodsX, 2020
We provide more technical details about the HLIBCov package, which is using parallel hierarchical (H-) matrices to: • Approximate large dense inhomogeneous covariance matrices with a log-linear computational cost and storage requirement. • Compute matrix-
Alexander Litvinenko, Ronald Kriemann, Marc G. Genton, Ying Sun, David E. Keyes   +4 more
doaj   +1 more source

Memory and Resting‐State Connectivity in Acute Transient Global Amnesia: A Case–Control fMRI Study

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background and Objectives Transient global amnesia (TGA) is a striking model of isolated amnesia. While hippocampal lesions are well described, the network‐level mechanisms and the precise neuropsychological profile remain debated. Our objective was thus to characterize functional and neuropsychological correlates of acute TGA and their ...
Elias El Otmani, Emmanuel Barbeau, Béatrice Lemesle, Emilie Milongo‐Rigal, Sophie Fernandez, Sandrine Charpentier, Jean‐François Albucher, Nicolas Raposo, Fabrice Bonneville, Patrice Péran, Jérémie Pariente   +10 more
wiley   +1 more source