Stone, M.; Brooks, R. J. Continuum regression: Cross-validated sequentially constructed prediction embracing ordinary least squares, partial least squares and principal components regression. (English) Zbl 0708.62054 J. R. Stat. Soc., Ser. B 52, No. 2, 237-269 (1990). Authors’ summary: The paper addresses the evergreen problem of construction of regressors for use in least squares muliple regression. In the context of a general sequential procedure for doing this, it is shown that, with a particular objective criterion for the construction, the procedures of ordinary least squares and principal components regression occupy the opposite ends of a continuous spectrum, with partial least squares lying in between. There are two adjustable ‘parameters’ controlling the procedure: ‘alpha’, in the continuum [0,1], and ‘omega’, the number of regressors finally accepted. These control parameters are chosen by cross validation. The method is illustrated by a range of examples of its application. Reviewer: J.Lillestøl Cited in 1 ReviewCited in 36 Documents MSC: 62J05 Linear regression; mixed models 62L12 Sequential estimation 62H25 Factor analysis and principal components; correspondence analysis Keywords:construction of regressors; least squares muliple regression; ordinary least squares; principal components regression; partial least squares; cross validation; examples PDFBibTeX XMLCite \textit{M. Stone} and \textit{R. J. Brooks}, J. R. Stat. Soc., Ser. B 52, No. 2, 237--269 (1990; Zbl 0708.62054)