On best affine unbiased covariance-preserving prediction of factor scores.

Neudecker, Heinz. "On best affine unbiased covariance-preserving prediction of factor scores.." SORT 28.1 (2004): 27-36. <http://eudml.org/doc/40448>.

@article{Neudecker2004,
abstract = {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 Ω of the observable scores vector and that of the unique factors, Ψ, to be singular. We require T' Ψ T &gt; 0, where T Λ T' is a Schur decomposition of Ω. As usual the variance of the common factors, Φ, and the loadings matrix A will have full column rank.},
author = {Neudecker, Heinz},
journal = {SORT},
keywords = {Análisis multivariante; Análisis factorial; Predicción estadística; factor analysis; factor scores; covariance-preserving; Kristof-type theorem},
language = {eng},
number = {1},
pages = {27-36},
title = {On best affine unbiased covariance-preserving prediction of factor scores.},
url = {http://eudml.org/doc/40448},
volume = {28},
year = {2004},
}

TY - JOUR
AU - Neudecker, Heinz
TI - On best affine unbiased covariance-preserving prediction of factor scores.
JO - SORT
PY - 2004
VL - 28
IS - 1
SP - 27
EP - 36
AB - 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 Ω of the observable scores vector and that of the unique factors, Ψ, to be singular. We require T' Ψ T &gt; 0, where T Λ T' is a Schur decomposition of Ω. As usual the variance of the common factors, Φ, and the loadings matrix A will have full column rank.
LA - eng
KW - Análisis multivariante; Análisis factorial; Predicción estadística; factor analysis; factor scores; covariance-preserving; Kristof-type theorem
UR - http://eudml.org/doc/40448
ER -