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http://dx.doi.org/10.5351/KJAS.2007.20.2.373

G-Inverse and SAS IML for Parameter Estimation in General Linear Model  

Choi, Kuey-Chung (Division of Mathematics, Computer Science and Statistics, Cho-Sun University)
Kang, Kwan-Joong (Department of Mathematics, Dong-A University)
Park, Byung-Jun (Division of Mathematics, Computer Science and Statistics, Cho-Sun University)
Publication Information
The Korean Journal of Applied Statistics / v.20, no.2, 2007 , pp. 373-385 More about this Journal
Abstract
The solution of the normal equation arising in a general linear model by the least square methods is not unique in general. Conventionally, SAS IML and G-inverse matrices are considered for such problems. In this paper, we provide a systematic solution procedures for SAS IML.
Keywords
Regular matrix; non-regular matrix; diagonal matrix; symmetric matrix; generalized invese matrix;
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