  This paper is an extension of Part I of a series about Nu-class
multifunctions. A method is presented for computing the integrated mean-squared
prediction error (IMSPE) in the design of computer experiments, when the
prediction domain is a circular disk. The method is extensible to more than two
factors, to prediction domains other than squares or disks, and to a variety of
assumed covariance functions. Three example optimal designs, under Gaussian
covariance with known hyperparameters, are found using the method: an n=1
design centered on the disk; an n=2 continuously rotatable design with assumed
inversion symmetry about the center of the disk; and an n=4 twin-point design
similar to the n=4 twin-point design observed previously for a square
prediction domain [1]. The four-point design on the disk demonstrates that
non-round boundaries are not a prerequisite for the occurrence of twin-point
optimal designs.
