Nearest neighbor analysis of point processes: Applications to multidimensional scaling

Amos Tversky, Yosef Rinott, Charles M. Newman

Research output: Contribution to journalArticle

Abstract

A new approach for evaluating spatial statistical models based on the (random) number 0 ≤ N(i, n) ≤ n of points whose nearest neighbor is i in an ensemble of n + 1 points is discussed. The second moment of N(i, n) offers a measure of the centrality of the ensemble. The asymptotic distribution of N(i, n) and the expected degree of centrality for several spatial and nonspatial point processes is described. The use of centrality as a diagnostic statistic for multidimensional scaling is explored.

Original languageEnglish (US)
Pages (from-to)235-250
Number of pages16
JournalJournal of Mathematical Psychology
Volume27
Issue number3
DOIs
StatePublished - 1983

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Centrality
Statistical Models
Point Process
Nearest Neighbor
Statistics
Scaling
Ensemble
Random number
Spatial Model
Statistical Model
Asymptotic distribution
Statistic
Diagnostics
Model-based
Moment

ASJC Scopus subject areas

  • Applied Mathematics
  • Experimental and Cognitive Psychology

Cite this

Nearest neighbor analysis of point processes : Applications to multidimensional scaling. / Tversky, Amos; Rinott, Yosef; Newman, Charles M.

In: Journal of Mathematical Psychology, Vol. 27, No. 3, 1983, p. 235-250.

Research output: Contribution to journalArticle

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