Results 21 to 30 of about 531,665 (271)

2D-DOA Estimation in Switching UCA Using Deep Learning-Based Covariance Matrix Completion

Sensors, 2022
In this paper, we study the two-dimensional direction of arrival (2D-DOA) estimation problem in a switching uniform circular array (SUCA), which means performing 2D-DOA estimation with a reduction in the number of radio frequency (RF) chains.
Ruru Mei, Ye Tian, Yonghui Huang, Zhugang Wang   +3 more
doaj   +1 more source

A Novel State Estimation Approach for Suspension System with Time-Varying and Unknown Noise Covariance

Actuators, 2023
In this paper, a novel state estimation approach based on the variational Bayesian adaptive Kalman filter (VBAKF) and road classification is proposed for a suspension system with time-varying and unknown noise covariance.
Qiangqiang Li, Zhiyong Chen, Wenku Shi
doaj   +1 more source

Estimating cosmological parameter covariance [PDF]

Monthly Notices of the Royal Astronomical Society, 2014
We investigate the bias and error in estimates of the cosmological parameter covariance matrix, due to sampling or modelling the data covariance matrix, for likelihood width and peak scatter estimators. We show that these estimators do not coincide unless the data covariance is exactly known. For sampled data covariances, with Gaussian distributed data
Taylor, Andy, Joachimi, Benjamin
openaire   +2 more sources

Shrinkage Estimators for Covariance Matrices [PDF]

Biometrics, 2001
Estimation of covariance matrices in small samples has been studied by many authors. Standard estimators, like the unstructured maximum likelihood estimator (ML) or restricted maximum likelihood (REML) estimator, can be very unstable with the smallest estimated eigenvalues being too small and the largest too big.
Daniels, Michael J., Kass, Robert E.
openaire   +3 more sources

Ionospheric Kalman Filter Assimilation Based on Covariance Localization Technique

Remote Sensing, 2022
The data assimilation algorithm is a common algorithm in space weather research. Based on the GNSS data from the China Crustal Movement Observation Network (CMONOC) and the International Reference Ionospheric Model (IRI), a fast three-dimensional (3D ...
Jiandong Qiao, Chen Zhou, Yi Liu, Jiaqi Zhao, Zhengyu Zhao   +4 more
doaj   +1 more source

SEMIPARAMETRIC ESTIMATION WITH GENERATED COVARIATES [PDF]

Econometric Theory, 2011
We study a general class of semiparametric estimators when the infinite-dimensional nuisance parameters include a conditional expectation function that has been estimated nonparametrically using generated covariates. Such estimators are used frequently to e.g., estimate nonlinear models with endogenous covariates when identification is achieved using ...
Mammen, Enno, Rothe, Christoph, Schienle, Melanie   +2 more
openaire   +14 more sources

Beta-Adjusted Covariance Estimation [PDF]

SSRN Electronic Journal, 2021
The increase in trading frequency of Exchanged Traded Funds (ETFs) presents a positive externality for financial risk management when the price of the ETF is available at a higher frequency than the price of the component stocks. The positive spillover consists in improving the accuracy of pre-estimators of the integrated covariance of the stocks ...
Boudt, Kris, Dragun, Kirill, Orimar, Sauri Arregui, Vanduffel, Steven   +3 more
openaire   +2 more sources

Data Fusion With Inverse Covariance Intersection for Prior Covariance Estimation of the Particle Flow Filter

IEEE Access, 2020
The prior covariance estimation method based on inverse covariance intersection (ICI) is proposed to apply the particle flow filter. The proposed method has better estimate performance and guarantees consistent estimation results compared with previous ...
Chang Ho Kang, Sun Young Kim, Jin Woo Song   +2 more
doaj   +1 more source

Generalized Covariance Estimator

Journal of Business & Economic Statistics, 2022
We consider a class of semi-parametric dynamic models with independent identically distributed errors, including the nonlinear mixed causal-noncausal Vector Autoregressive (VAR), Double-Autoregressive (DAR) and stochastic volatility models. To estimate the parameters characterizing the (nonlinear) serial dependence, we introduce a generic Generalized ...
Gourieroux, Christian, Jasiak, Joann
openaire   +2 more sources

SPICE-ML Algorithm for Direction-of-Arrival Estimation

Sensors, 2019
Sparse iterative covariance-based estimation, an iterative direction-of-arrival approach based on covariance fitting criterion, can simultaneously estimate the angle and power of incident signal.
Yu Zheng, Lutao Liu, Xudong Yang
doaj   +1 more source