Netscal: A Network Scaling Algorithm for Nonsymmetric Proximity Data
- 1 March 1989
- journal article
- Published by Cambridge University Press (CUP) in Psychometrika
- Vol. 54 (1) , 25-51
- https://doi.org/10.1007/bf02294447
Abstract
A simple property of networks is used as the basis for a scaling algorithm that represents nonsymmetric proximities as network distances. The algorithm determines which vertices are directly connected by an arc and estimates the length of each arc. Network distance, defined as the minimum pathlength between vertices, is assumed to be a generalized power function of the data. The derived network structure, however, is invariant across monotonic transformations of the data. A Monte Carlo simulation and applications to eight sets of proximity data support the practical utility of the algorithm.Keywords
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