trading

Data from the New Geographical Digest (1986) analyzed in Cox and Cox (2001). For 20 countries their main trading partners were dichotomously scored (1 = trade performed, 0 = trade not performed). 
Based on this dichotomous matrix the dissimilarities were computed using the Jaccard coefficient.

datasets

Implements the following approaches for multidimensional scaling (MDS) based on stress minimization using majorization (smacof): ratio/interval/ordinal/spline MDS on symmetric dissimilarity matrices, MDS with external constraints on the configuration, individual differences scaling (idioscal, indscal), MDS with spherical restrictions, and ratio/interval/ordinal/spline unfolding (circular restrictions, row-conditional). Various tools and extensions like jackknife MDS, bootstrap MDS, permutation tests, MDS biplots, gravity models, unidimensional scaling, drift vectors (asymmetric MDS), classical scaling, and Procrustes are implemented as well.

Patrick Mair

smacof

Multidimensional Scaling

Jan De Leeuw

Patrick J. F. Groenen

Ingwer Borg

trading function

Object of class <code>"dist"</code> with dissimilarities of the following countries:
Arge: Argentina
Aust: Australia
Braz: Brazil
Cana: Canada
Chin: China
Czec: Czechoslovakia
Egyp: Egypt
E.Ge: East Germany
Fran: France
Hung: Hungary
Indi: India
Ital: Italy
Japa: Japan
N.Ze: New Zealand
Pola: Poland
Swed: Sweden
USA
USSR: Soviet Union
U.K.: United Kingdom
W.Ge: West Germany

Format

Trading data — trading

Trading data

trading: Trading data

Description

Usage

Arguments

Format

References

Examples