Results 81 to 90 of about 296,448 (209)

Analysis of covariance [PDF]

American Journal of Orthodontics and Dentofacial Orthopedics, 2016
openaire   +4 more sources

Application of the covariance analysis by the “sliding window” method to assess the relationship of non-stationary time series

Экспериментальная психология
A covariance analysis method is described to solve the problem of estimating the dynamics of the relationship between two non-stationary time series, represented by behavioral and/or physiological data.
V.V. Apanovich, D.L. Gladilin
doaj   +1 more source

Relativistic covariance and nonlinear quantum mechanics: Tomonaga-Schwinger analysis

Physics Letters B
We use the Tomonaga–Schwinger (TS) formulation of quantum field theory to determine when state-dependent additions to the local Hamiltonian density (i.e., modifications to linear Schrödinger evolution) violate relativistic covariance.
Stephen D.H. Hsu
doaj   +1 more source

Testing of a Structures Covariance Matrix for Three-Level Repeated Measures Data. [PDF]

This paper considers the problem of estimating, and testing for, a Kronecker product covariance structure of three-level (multiple time points (p), multiple sites (u), and multiple response variables (q)) multivariate data.
Ricardo Leiva, Anuradha Roy
core  

The Effects of Data Imputation on Covariance and Inverse Covariance Matrix Estimation

IEEE Access
Various data analysis techniques and procedures (correlation heatmap, linear discriminant analysis, quadratic discriminant analysis) rely on the estimation of the covariance matrix or its inverse (the precision matrix).
Tuan L. Vo, Quan Huu Do, Thu Nguyen, Pal Halvorsen, Michael A. Riegler, Binh T. Nguyen   +5 more
doaj   +1 more source

Covariance Tracking via Geometric Particle Filtering [PDF]

, 2009
Region covariance descriptor recently proposedhas has been approved robust and elegant to describe a region of interest, which has been applied to visual tracking.
Liu YP(刘云鹏), Shi HY(史洪岩), Wang GG(王国刚)   +2 more
core  

Canonical analysis based on scatter matrices. [PDF]

In this paper, the influence functions and limiting distributions of the canonical correlations and coefficients based on affine equivariant scatter matrices are developed for elliptically symmetric distributions.
Croux, Christophe, Kankainen, A, Taskinen, S, Ollila, E, Ona, H   +4 more
core  

The K-Step Spatial Sign Covariance Matrix [PDF]

The Sign Covariance Matrix is an orthogonal equivariant estimator of mul- tivariate scale. It is often used as an easy-to-compute and highly robust estimator.
Yadine, A., Croux, C., Dehon, C.
core   +1 more source

The Kullback–Leibler Divergence and the Convergence Rate of Fast Covariance Matrix Estimators in Galaxy Clustering Analysis

The Astrophysical Journal
We present a method to quantify the convergence rate of the fast estimators of the covariance matrices in the large-scale structure analysis. Our method is based on the Kullback–Leibler (KL) divergence, which describes the relative entropy of two ...
Zhigang Li, Zhejie Ding, Yu Yu, Pengjie Zhang   +3 more
doaj   +1 more source

Large-scale portfolios using realized covariance matrix: evidence from the Japanese stock market [PDF]

This paper examines effects of realized covariance matrix estimators based on high-frequency data on large-scale minimum-variance equity portfolio optimization.
Masato Ubukata
core   +3 more sources