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Multiple Regression with a Singular Matrix
Author(s) -
Healy M. J. R.
Publication year - 1968
Publication title -
journal of the royal statistical society: series c (applied statistics)
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.205
H-Index - 72
eISSN - 1467-9876
pISSN - 0035-9254
DOI - 10.2307/2985675
Subject(s) - mathematics , statistics , regression , regression analysis , matrix (chemical analysis) , econometrics , chromatography , chemistry
Summary In certain applications of multiple regression the coefficient matrix of the normal equations is singular and therefore does not possess an inverse. Recent theoretical developments make it possible to broaden the theory of least squares so as to include this situation without having to treat it as a special case, and these can be paralleled by appropriate numerical techniques. This paper gives a survey of these developments and outlines some of their possible applications.