Results 101 to 110 of about 192,768 (193)

Smooth Interpolation of Covariance Matrices and Brain Network Estimation

IEEE Transactions on Automatic Control, 2019
We propose an approach to use the state covariance of autonomous linear systems to track time-varying covariance matrices of nonstationary time series. Following concepts from the Riemannian geometry, we investigate three types of covariance paths obtained by using different quadratic regularizations of system matrices. The first quadratic form induces
openaire   +3 more sources

Estimation of Singular Covariance Matrices of Random Effects

Journal of Dairy Science, 1986
Abstract The variance-covariance matrix of random effects in a mixed linear model can be singular because identical twins are used or because a base population has been selected. As a consequence, the usual mixed model equations cannot be used for estimation and prediction.
openaire   +1 more source

Research on AUV Underwater Localization Method Based on an n-Shaped Array. [PDF]

Sensors (Basel)
Han C, Gao M, Shen T, Guo C.
europepmc   +1 more source

Multivariate Regression With Dependence Structures: Evaluating Associations Between Plasma Metabolomics and Alcohol Intake in Older Adults. [PDF]

Stat Med
Yang Y, Chen C, Lee H, Wang M, Zhang Y, Chen S.   +5 more
europepmc   +1 more source

Bridging developmental and statistical approaches to variation and evolution. [PDF]

Proc Natl Acad Sci U S A
Milocco L, Uller T.
europepmc   +1 more source

An Unscented Kalman Filter Based on the Adams-Bashforth Method with Applications to the State Estimation of Osprey-Type Drones Composed of Tiltable Rotor Mechanisms. [PDF]

Sensors (Basel)
Watanabe K, Takeda S, Nagai I.
europepmc   +1 more source

Studies in Estimation of Patterned Covariance Matrices

, 2009
Many testing, estimation and confidence interval procedures discussed in the multivariate statistical literature are based on the assumption that the observation vectors are independent and normally distributed. The main reason for this is that often sets of multivariate observations are, at least approximately, normally distributed.
openaire   +1 more source

Deep Robust Moving Horizon Estimation for Nonlinear Multi-Rate Systems. [PDF]

Sensors (Basel)
Wang R, Wen S, Chen B.
europepmc   +1 more source

Information-Theoretic Dual Adaptive Control Revisited: Multivariable Extension with Applications to Fault-Tolerant Control. [PDF]

Entropy (Basel)
Yamé JJ.
europepmc   +1 more source

Recursive Batch Smoother with Multiple Linearization for One Class of Nonlinear Estimation Problems: Application for Multisensor Navigation Data Fusion. [PDF]

Sensors (Basel)
Stepanov O, Isaev A, Dranitsyna E, Litvinenko Y.   +3 more
europepmc   +1 more source