✦ LIBER ✦

Probabilistic Multidimensional Scaling Using a City-Block Metric

✍ Scribed by David B. MacKay

Publisher: Elsevier Science
Year: 2001
Tongue: English
Weight: 222 KB
Volume: 45
Category: Article
ISSN: 0022-2496
DOI: 10.1006/jmps.2000.1311

No coin nor oath required. For personal study only.

✦ Synopsis

Using a probabilistic model, exact and approximate probability density functions (PDFs) for city-block distances and distance ratios are developed. The model assumes that stimuli can be represented by random vectors having multivariate normal distributions. Comparisons with the more common Euclidean PDFs are presented. The potential ability of the proposed model to correctly detect Euclidean and city-block metrics is briefly investigated. These results are then contrasted to those obtained using a deterministic, nonmetric model.

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