The Cholesky Factorization of the Inverse Correlation or Covariance Matrix in Multiple Regression
From MaRDI portal
Publication:3963888
DOI10.2307/1268678zbMath0498.62057OpenAlexW4233350171MaRDI QIDQ3963888
Douglas M. Hawkins, W. J. R. Eplett
Publication date: 1982
Full work available at URL: https://doi.org/10.2307/1268678
Cholesky factorizationcovariance matrixsubset selectioninteractive computingmultiple regressionCIRinverse correlationlatent-root regression analysislower-triangular Cholesky inverse root
Multivariate analysis (62H99) Linear regression; mixed models (62J05) Factorization of matrices (15A23)
Related Items (10)
Anderson acceleration of the alternating projections method for computing the nearest correlation matrix ⋮ Signal and image processing of physiological data: methods for diagnosis and treatment purposes ⋮ Influence curve for the choesky root of a coveriance matrix ⋮ Application of the Moore-Penrose inverse of a data matrix in multiple regression ⋮ Variance analysis of identified linear MISO models having spatially correlated inputs, with application to parallel Hammerstein models ⋮ Numerical Analysis of a Correlation Matrix ⋮ Usage of Cholesky decomposition in order to decrease the nonlinear complexities of some nonlinear and diversification models and present a model in framework of mean-semivariance for portfolio performance evaluation ⋮ A UNIFIED APPROACH TO ARMA MODEL IDENTIFICATION AND PRELIMINARY ESTIMATION ⋮ Stability of the inverse correlation matrix. Partial ridge regression ⋮ All possible subset regressions using the triangular decomposition
This page was built for publication: The Cholesky Factorization of the Inverse Correlation or Covariance Matrix in Multiple Regression