Tuning the Parameters for Precision Matrix Estimation Using Regression Analysis
Precision matrix, i.e., inverse covariance matrix, is widely used in signal processing, and often estimated from training samples. Regularization techniques, such as banding and rank reduction, can be applied to the covariance matrix or precision matrix estimation for improving the estimation accura...
Main Authors: | Jun Tong, Jiayi Yang, Jiangtao Xi, Yanguang Yu, Philip O. Ogunbona |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2019-01-01
|
Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/8755295/ |
Similar Items
-
Study on the Curvature Reducing Method of Non-linear Regression Model
by: Wu Jin-mei, et al.
Published: (2016-01-01) -
LOCALLY REGULARIZED LINEAR REGRESSION IN THE VALUATION OF REAL ESTATE
by: Mariusz Kubus
Published: (2016-09-01) -
Identification of Radioactive Isotopes Using Cholesky-Decomposition of Matrices
by: Hanka László
Published: (2020-03-01) -
Contributions to Large Covariance and Inverse Covariance Matrices Estimation
by: Kang, Xiaoning
Published: (2018) -
Calculating the true level of predictors significance when carrying out the procedure of regression equation specification
by: Nikita A. Moiseev
Published: (2017-07-01)