  One classical measure of the quality of an interpolating function is its
Lipschitz constant. In this paper we consider interpolants with additional
smoothness requirements, in particular that their derivatives be Lipschitz. We
show that such a measure of quality can be easily computed, giving two
algorithms, one optimal in the dimension of the data, the other optimal in the
number of points to be interpolated.
