  While matching procedures based on pairwise distances are conceptually
appealing and thus favored in practice, theoretical guarantees for such
procedures are rarely found in the literature. We propose and analyze matching
procedures based on distance profiles that are easily implementable in
practice, showing these procedures are robust to outliers and noise. We
demonstrate the performance of the proposed method using a real data example
and provide simulation studies to complement the theoretical findings.
