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Deletion, augmentation and principal predictors

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  • Jensen, D. R.

Abstract

Effects of augmenting or deleting sets of design points are studied using principal components of the predictive dispersion at those points. The affected linear parameters are then given explicitly in terms of design points and coefficients defining the principal predictors. In addition to structural links, this approach offers computational advantages as well. The methods are illustrated numerically for second-order models using central composite designs.

Suggested Citation

  • Jensen, D. R., 1996. "Deletion, augmentation and principal predictors," Statistics & Probability Letters, Elsevier, vol. 29(3), pages 263-270, September.
    • Handle: RePEc:eee:stapro:v:29:y:1996:i:3:p:263-270
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