On best affine unbiased covariance-preserving prediction of factor scores

This paper gives a generalization of results presented by ten Berge, Krijnen, Wansbeek & Shapiro. They examined procedures and results as proposed by Anderson & Rubin, McDonald, Green and Krijnen, Wansbeek & ten Berge. We shall consider the same matter, under weaker rank assumptions. We...

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Detalles Bibliográficos
Autor: Neudecker, Heinz
Tipo de recurso: artículo
Fecha de publicación:2004
País:España
Institución:Universitat Politècnica de Catalunya (UPC)
Repositorio:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglés
OAI Identifier:oai:upcommons.upc.edu:2099/3746
Acceso en línea:https://hdl.handle.net/2099/3746
Access Level:acceso abierto
Palabra clave:Multivariate analysis
Algebras, Linear
Multilinear algebra
Matrices
Anàlisi multivariable
Àlgebra lineal
Àlgebra multilineal
Matriu S, Teoria
Classificació AMS::15 Linear and multilinear algebra
matrix theory
Classificació AMS::62 Statistics::62H Multivariate analysis
Descripción
Sumario:This paper gives a generalization of results presented by ten Berge, Krijnen, Wansbeek & Shapiro. They examined procedures and results as proposed by Anderson & Rubin, McDonald, Green and Krijnen, Wansbeek & ten Berge. We shall consider the same matter, under weaker rank assumptions. We allow some moments, namely the variance of the observable scores vector and that of the unique factors,to be singular. We require T′ T > 0, where T T′ is a Schur decomposition of. As usual the variance of the common factors, , and the loadings matrix Awill have full column rank.