Maximum likelihood factor analysis with rank-deficient sample covariance matrices
Maximum likelihood factor analysis with rank-deficient sample covariance matrices
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DOI：
10.1016/j.jmva.2006.11.012
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发表时间：
2007-04-01
影响因子：
1.6
通讯作者：
Symons, James
中科院分区：
文献类型：
--
作者：
Robertson, Donald;Symons, James
本文充分刻画了样本协方差阵秩亏时因子模型的极大似然估计可行的情形。当变量的数量超过观测的数量时，就会出现这种情况。(c)2006年爱思唯尔公司All rights reserved.
This paper characterises completely the circumstances in which maximum likelihood estimation of the factor model is feasible when the sample covariance matrix is rank deficient. This situation will arise when the number of variables exceeds the number of observations. (c) 2006 Elsevier Inc. All rights reserved.