Abstract
Abstract The standard cubic spline regression method is shown to be a special case of the restricted least-squares estimator. The equivalence of the two procedures under a common set of restrictions is proved. The greater flexibility of the restricted least-squares estimator in terms of the number of restrictions and tests of hypotheses that can be utilized is illustrated by an application to a set of data that has been previously analyzed by the spline method.
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