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Journal of Classification

, Volume 7, Issue 1, pp 115–158 | Cite as

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  • John Haslett
  • Victor Kamensky
  • Richard C. Dubes
  • Norman Cliff
  • Jan de Leeuw
  • Robert F. Ling
  • William H. E. Day
  • John Daws
  • C. Perruchet
  • Ivo W. Molenaar
  • F. Murtagh
  • Anuska Ferilgoj
Article
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References

  1. CLEVELAND, W. S. (1985),The Elements of Graphing Data, Pacific Grove, CA: Wadsworth.Google Scholar
  2. DONOHO, A. W., DONOHO, D. L., GASKO, M., KERICK, D. W., and OLSEN, C.W. (1988),Macspin, Version 2.0, Austin, TX:D 2 Software.Google Scholar
  3. TUFTE, E. R. (1983),The Visual Display of Quantitative Information, Cheshire, CT: Graphics Press.Google Scholar
  4. TUKEY, J. W. (1977),Exploratory Data Analysis, Reading, MA: Addison-Wesley.Google Scholar
  5. VELLEMAN, P. F., and VELLEMAN, A. Y. (1988),DataDesk Professional, Northbrook, IL: Odesta Corporation.Google Scholar

References

  1. BRAVERMAN, E. M. and MUCHNIK, I. B. (1983),Structural Methods for Analysis of Empirical Data, Moscow: Nauka (in Russian).Google Scholar
  2. MANDEL, I. D. (1987), “Duality in the Classification Problem,”Automation and Remote Control, 48, 107–110.Google Scholar
  3. MANDEL, I. D. and CHERNYI, L. B. (1988), “Experimental Comparison of Cluster Analysis Algorithms,”Automation and Remote Control, 49, 87–94.Google Scholar
  4. MIRKIN, B. G. (1975), “On the Problem of Reconciling Partitions,” inQuantitative Sociology: International Perspectives on Mathematical and Statistical Modeling, Eds. H. M. Blalock, A. Aganbegian, F. M. Borodkin, R. Boudon, and V. Capecchi, New York: Academic Press, 441–449.Google Scholar
  5. MIRKIN, B. G. (1985),Classification in Social and Economic Research, Moscow: Finansy and Statistika Publishers (in Russian).Google Scholar
  6. MIRKIN, B. G. (1987), “Additive Clustering and Qualitative Factor Analysis Methods for Similarity Matrices,”Journal of Classification, 4, 7–31.Google Scholar
  7. MUCHNIK, I. B., CHKUASELI, N. F., and SHVARTSER, L. V. (1986), “A Linguistic Analysis of 0–1 Matrices Using Monotone Systems,”Automation and Remote Control, 47, 553–560.Google Scholar
  8. SATAROV, G. A. (1981), “A Comparison of Two Scaling Algorithms for Binary Data,” inMathematical Methods in Sociological Research, Moscow: Nauka, 90–98 (in Russian).Google Scholar
  9. SHUSTOROVITZ, A. M. (1977), “Adequate Similarity Measures in Pattern Recognition with Mixed Set of Variables,” inProblems of Information Processing in System Planning, Novosibirsk, 147–152 (in Russian).Google Scholar
  10. ZAKS, Y. M. and MUCHNIK, I. B. (1989), “Monotone Systems for Incomplete Classification of a Finite Sets of Objects,”Automation and Remote Control, 50, 155–164 (pages are given for Russian edition, April 1989).Google Scholar

References

  1. DIJKSTRA, E. W. (1989), “On the Cruelty of Really Teaching Computing Science,”Communications of the ACM, 32, 1398–1404.Google Scholar
  2. DUDA, R. O. and HART, P. E. (1973),Pattern Classification and Scene Analysis, New York: John Wiley & Sons.Google Scholar
  3. VAN LAARHOVEN, P.J.M. and AARTS, E. H. L. (1987),Simulated Annealing: Theory and Applications, Dordrecht, Holland: Reidel Publishing Company.Google Scholar

References

  1. ANDERSON, T. W. (1959), “Some Scaling Models and Estimation Procedures in the Latent Class Model,” inProbability and Statistics, The Harald Cramér Volume, Ed., U. Grenander, Stockholm: Almqvist and Wicksell.Google Scholar
  2. LAZARSFELD, P. F., and HENRY, N. W. (1968),Latent Structure Analysis, New York: Houghton-Mifflin.Google Scholar
  3. LAWLEY, D. N., and MAXWELL, A. E. (1963, 1971),Factor Analysis as a Statistical Method, London: Butterworth.Google Scholar
  4. MCDONALD, R. P. (1962), “A Note on the Derivation of the General Latent Class Model,”Psychometrika, 27, 203–206.Google Scholar

Reference

  1. GODEHART, E. (1988),Graphs as Structural Models, Advances in System Analysis Series, D.P.F. Möller (Ed.), Vol. 4, Braunschweig/Wiesbaden: Vieweg.Google Scholar

References

  1. JARDINE, N., and SIBSON, R. (1968a), “A Model for Taxonomy,”Mathematical Biosciences, 2, 465–482.Google Scholar
  2. JARDINE, N., and SIBSON, R. (1968b), “The Construction of Hierarchic and Nonhierarchic Classifications,”Computer Journal, 11, 177–184.Google Scholar
  3. LING, R. F. (1972), “On the Theory and Construction of k-Clusters,”Computer Journal, 15, 326–332.Google Scholar
  4. LING, R. F. (1973), “A Probability Theory for Cluster Analysis,”Journal of the American Statistical Association, 68, 159–164.Google Scholar
  5. MATULA, D. W. (1972), “k-Components, Clusters and Slicings in Graphs,”SIAM Journal of Applied Mathematics, 22, 459–480.Google Scholar
  6. SNEATH, P. H. A., and SOKAL, R. R. (1973),Numerical Taxonomy: The Principles and Practice of Numerical Classification, San Francisco: W.H. Freeman, xv + 573 p.Google Scholar
  7. SOKAL, R. R., and SNEATH, P. H. A. (1963),Principles of Numerical Taxonomy, San Francisco: W. H. Freeman, xvi + 359 p.Google Scholar

References

  1. BERTRAND, P. (1986), Etude de la Représentation Pryamidale, Thesis, Université Paris IX — Dauphine.Google Scholar
  2. DIDAY, E. et al. (1980),Optimisation en Classification Automatique, Le Chesnay: INRIA.Google Scholar
  3. DIDAY, E. (1986), “Une Représentation Visuelle des Classes Empiètantes: les Pyramides,”RAIRO-APII, 20, 465–526.Google Scholar
  4. ESCOFIER, B. and PAGÈS, J. (1988),Analyses Factorielles Simples et Multiples: Objectifs, Méthodes et Interprétation, Paris: Dunod.Google Scholar
  5. GORDON, A. D. (1981),Classification, London: Chapman and Hall.Google Scholar
  6. JAMBU, M. and LEBEAUX, M. O. (1983),Cluster Analysis and Data Analysis, Amsterdam: North-Holland.Google Scholar
  7. LEBART, L., MORINEAU, A., and WARWICK, K. (1984),Multivariate Descriptive Statistical Analysis, New York: Wiley.Google Scholar
  8. MACQUEEN, J. B. (1967), “Some Methods for Classification and Analysis of Multivariate Observations,” in L. M. LeCam and J. Neyman (Eds.),Proceedings of the 5th Berkeley Symposium, Volume1, 281–297.Google Scholar

Reference

  1. HWANG, K. and DEGROOT, D., Eds. (1989),Parallel Processing for Supercomputers and Artificial Intelligence, New York: McGraw-Hill.Google Scholar

Copyright information

© Springer-Verlag New York Inc 1990

Authors and Affiliations

  • John Haslett
    • 1
  • Victor Kamensky
    • 2
  • Richard C. Dubes
    • 3
  • Norman Cliff
    • 4
  • Jan de Leeuw
    • 5
  • Robert F. Ling
    • 6
    • 7
  • William H. E. Day
    • 8
  • John Daws
    • 9
  • C. Perruchet
    • 10
  • Ivo W. Molenaar
    • 11
    • 12
  • F. Murtagh
    • 13
    • 14
  • Anuska Ferilgoj
    • 15
  1. 1.Department of StatisticsTrinity CollegeDublin 2Ireland
  2. 2.Department of Epidemiology and Social Medicine, Belfer BuildingAlbert Einstein College of MedicineBronx
  3. 3.Computer Science DepartmentMichigan State UniversityEast LansingUSA
  4. 4.Department of PsychologyUniversity of Southern CaliforniaLos AngelesUSA
  5. 5.Department of PsychologyUniversity of California Los AngelesLos AngelesUSA
  6. 6.Harvard UniversityUSA
  7. 7.Department of Mathematical SciencesClemson UniversityClemsonUSA
  8. 8.Department of Computer ScienceMemorial University of NewfoundlandSt. John'sCanada
  9. 9.Department of PsychologyUniversity of IllinoisChampaignUSA
  10. 10.UTAC, Autodrome, LinasMontlhéryFrance
  11. 11.S&M FPPSWGroningenNetherlands
  12. 12.University of GroningenNetherlands
  13. 13.Space Telescope - European Coordinating FacilityEuropean Southern ObservatoryGarchingW. Germany
  14. 14.Astrophysics Div., Space Science Dept.European Space AgencyGermany
  15. 15.Department of SociologyEdvard Kardelj University, LjubljanaLjubljanaYugoslavia

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