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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| 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 |
| 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. |
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