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http://dx.doi.org/10.5351/CKSS.2008.15.3.333

Variable Selection Theorem for the Analysis of Covariance Model  

Yoon, Sang-Hoo (Department of Statistics, Chonnam National University)
Park, Jeong-Soo (Department of Statistics, Chonnam National University)
Publication Information
Communications for Statistical Applications and Methods / v.15, no.3, 2008 , pp. 333-342 More about this Journal
Abstract
Variable selection theorem in the linear regression model is extended to the analysis of covariance model. When some of regression variables are omitted from the model, it reduces the variance of the estimators but introduces bias. Thus an appropriate balance between a biased model and one with large variances is recommended.
Keywords
Estimable function; generalized inverse; mean squared error; positive semi-definite matrix; reduced model;
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Times Cited By KSCI : 4  (Citation Analysis)
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