Covariance matrix reconstruction

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Evaluating covariance matrix forecasts in a value-at-risk framework [PDF]

Covariance matrix forecasts of financial asset returns are an important component of current practice in financial risk management. A wide variety of models, ranging from matrices of simple summary measures to covariance matrices implied from option ...
Christian A. Walter, Jose A. Lopez
core

A Regression-Based Interpretation of the Inverse of the Sample Covariance Matrix [PDF]

, 2014
The usefulness of covariance and correlation matrices is well-known in various academic fields. Matrix inversion, if required in an analytical setting, tends to mask the intuition in interpreting the corresponding empirical or experimental results ...
Clarence C. Y. Kwan
core

Robust Gridless Two-Dimensional DOA Estimation via Covariance Reconstruction for Programmable Metasurface

Programmable metasurfaces enable two-dimensional direction-of-arrival (DOA) estimation using reconfigurable coding instead of fully digital element-wise sampling.
Qin Zhang +4 more
core +1 more source

A Smooth Reconstruction of Covariance Kernels from Fragmented Functional Data

Estimating the covariance operator from incomplete observations is a known problem in functional data analysis. While existing methods provide consistent estimates of the operator when functional samples are partially observed on varying subintervals of ...
Bortolotti, Teresa +3 more
core +1 more source

Toeplitz-Hankel Structured Covariance Reconstruction for DOA Estimation of Coherent Sources with Coprime Arrays Under Nonuniform Noise. [PDF]

Sensors (Basel)
Zhao H, Hu Y, Zhang Z, Zhang F.
europepmc +1 more source

Efficient Hamiltonian, structure and trace distance learning of Gaussian states. [PDF]

Nat Commun
Fanizza M, Rouzé C, Stilck França D.
europepmc +1 more source

Quantization-Aware Hybrid Anti-Interference Receiver for Partially Connected Arrays with Low-Resolution ADCs. [PDF]