統計学輪講（第２９回）

日時    2004年 11月  2日(火)　15時〜16時40分
場所    経済学部新棟３階第３教室
講演者  Prof. T. W. Anderson(Stanford University)
演題    Reduced Rank Regression and Blocks of Simultaneous Equations
概要：
Reduced rank regression analysis provides maximum likelihood estimators of 
a matrix of regression coefficients of specified rank and of corresponding 
linear restrictions on such matrices. These estimators depend on the 
eigenvectors of an "effect" matrix in the metric of an error covariance 
matrix. In this paper it is shown that the maximum likelihood estimator 
of the restrictions can be approximated by a function of the effect matrix 
alone. The procedures are applied to a block of simultaneous equations.
The block may be over-identified in the entire model and the individual 
equations just-identified within the block. The procedures are 
generalizations of the Limited Information Maximum Likelihood and Two-Stage 
Least Squares estimators.

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Tokyo University