Abstract
Stability of the Multidimensional Scaling (MDS) procedure is investigated under conditions where the dissimilarity data matrix involves small errors, in particular, in a somewhat ideal stochastic error model. The asymptotic performances of the solution of MDS and some related statistics are studied by using their asymptotic expansions under the model. Numerical examples which illustrate our theory are also given.
