On prediction and the power transformation family Academic Article

abstract

• The power transformation family is often used for transforming to a normal linear model. The variance of the regression parameter estimators can be much larger when the transformation parameter is unknown and must be estimated, compared to when the transformation parameter is known. We consider prediction of future untransformed observations when the data can be transformed to a linear model. When the transformation must be estimated, the prediction error is not much larger than when the parameter is known. 1981 Biometrika Trust.

authors

• Carroll, Raymond

published proceedings

• Biometrika

altmetric score

• 3

author list (cited authors)

• CARROLL, R. J., & RUPPERT, D.

citation count

• 86

complete list of authors

• CARROLL, RJ||RUPPERT, DAVID

publication date

• December 1981

publisher

• Oxford University Press (OUP)  Publisher

published in

• Biometrika  Journal

keywords

• 49 Mathematical Sciences
• 4905 Statistics

Digital Object Identifier (DOI)

• 10.1093/biomet/68.3.609

start page

• 609

end page

• 615

volume

• 68

issue

• 3

URL

• http%3A%2F%2Fdx.doi.org%2F10.1093%2Fbiomet%2F68.3.609