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Journal of Classification

, Volume 4, Issue 2, pp 245–278 | Cite as

Book reviews

  • Malcolm McLaren Dow
  • Peter Willett
  • Roderick P. McDonald
  • Belver C. Griffith
  • Michael Greenacre
  • Peter G. Bryant
  • Daniel Wartenberg
  • Ove Frank
Article
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References

  1. DIETZ, E.J. (1983), “Permutation Tests for Association Between Two Distance Matrices,”Systematic Zoology, 32, 21–26.Google Scholar
  2. DOW, M.M., CHEVERUD, J.C., and FRIEDLAENDER, J. (1987), “Partial Correlation of Distance Matrices in Studies of Population Structure,”American Journal of Physical Anthropology, 72, 343–352.Google Scholar
  3. FAUST, K., and ROMNEY, A.K. (1985), “The Effect of Skewed Distributions on Matrix Permutation Tests,”British Journal of Mathematical and Statistical Psychology, 38, 152–160.Google Scholar
  4. GOWER, J.C. (1971), “Statistical Methods of Comparing Different Multivariate Analyses of the Same Data,” inMathematics in the Archaeological and Historical Sciences, eds. F.R. Hodson, D.G. Kendall, and P. Tautu, Edinburgh: Edinburgh University Press, 138–149.Google Scholar
  5. HUBERT, L.J. (1983), “Inference Procedures for the Evaluation and Comparison of Proximity Matrices,” inNumerical Taxonomy, ed. J. Felsenstein, New York: Springer-Verlag, 209–228.Google Scholar
  6. HUBERT, L.J. (1984), “Statistical Applications of Linear Assignment,”Psychometrika, 49, 449–473.MathSciNetGoogle Scholar
  7. HUBERT, L.J., and SCHULTZ, J. (1976), “Quadratic Assignment as a General Data Analysis Strategy,”British Journal of Mathematical and Statistical Psychology, 29, 190–241.Google Scholar
  8. KRACKHARDT, D. (1987a), “QAP Partialling as a Test of Spuriousness,”Social Networks, 9, 171–186.Google Scholar
  9. KRACKHARDT, D. (1987b), “A Caveat on the Use of the Quadratic Assignment Procedure,”Psychometrika, (in Press).Google Scholar
  10. MANTEL, N. (1967), “The Detection of Disease Clustering and a Generalized Regression Approach,”Cancer Research, 27, 209–220.Google Scholar
  11. MIELKE, P.W., BERRY, K.J., and BRIER, G.W. (1981), “Application of Multi-response Permutation Procedures for Examining Seasonal Changes in Monthly Mean Sea-Level Pressure Patterns,”Monthly Weather Review, 109, 120–126.Google Scholar
  12. SCHONEMANN, P.H., and CARROLL, R.M. (1970), “Fitting One Matrix to Another Under Choice of a Central Dilation and a Rigid Motion,”Psychometrika, 35, 245–255.Google Scholar
  13. SMOUSE, P.E., LONG, J.C., and SOKAL, R.R. (1986), “Multiple Regression and Correlation Extensions of the Mantel Test of Matrix Correspondence,”Systematic Zoology, 35, 627–632.Google Scholar
  14. SNEATH, P.H., and SOKAL, R.R. (1973),Numerical Taxonomy, San Francisco: Freeman.Google Scholar
  15. SOKAL, R.R., and ROHLF, F.J. (1962), “The Comparison of Dendrograms by Objective Methods,”Taxon, 11, 33–40.Google Scholar
  16. SOKAL, R.R., SMOUSE, P.E., and NEEL, J.V. (1986), “The Genetic Structure of a Tribal Population, the Yanomama Indians. XV. An Effort to Find Pattern by Autocorrelation Analysis,”Genetics, 114, 259–287.Google Scholar
  17. SOKAL, R.R., and WARTENBERG, D.E. (1983), “A Test of Spatial Autocorrelation Using an Isolation-by-Distance Model,”Genetics, 105, 219–237.Google Scholar

References

  1. HARTIGAN, J. A. (1975),Clustering Algorithms, New York: Wiley.Google Scholar
  2. MURTAGH, F. (1983), “A Survey of Recent Advances in Hierarchical Clustering Algorithms,”Computer Journal, 26, 354–359.Google Scholar
  3. MURTAGH, F. (1984a), “Complexities of Hierarchic Clustering Algorithms: State of the Art,”Computational Statistics Quarterly, 1, 101–113.Google Scholar
  4. MURTAGH, F. (1984b), “A Review of Fast Techniques for Nearest Neighbour Searching,”COMPSTAT 1984, Vienna: Physica-Verlag.Google Scholar
  5. MURTAGH, F. (1985), “A Survey of Algorithms for Contiguity-Constrained Clustering and Related Problems,”Computer Journal, 28, 82–88.Google Scholar
  6. NOREAULT, T., KOLL, M., and MC GILL, M. J. (1977), “Automatic Ranked Output from Boolean Searches in SIRE,”Journal of the American Society for Information Science, 28, 333–339.Google Scholar
  7. SPATH, H. (1980),Cluster Analysis Algorithms, Chichester: Ellis Horwood.Google Scholar
  8. VOORHEES, E. M. (1986), “Implementing Agglomerative Hierarchic Clustering Algorithms for Use in Document Retrieval,”Information Processing and Management, 22, 465–476.Google Scholar

References

  1. MCDONALD, R. P. (1968), “A Unified Treatment of the Weighting Problem,”Psychometrika, 33, 351–381.Google Scholar
  2. MCDONALD, R. P. (1983), “Alternative Weights and Invariant Parameters in Optimal Scaling,”Psychometrika, 48, 377–391.Google Scholar

References

  1. SALTON, G., and MCGILL, M. J. (1983),Introduction to Information Retrieval, New York: McGraw-Hill.Google Scholar
  2. SARACEVIC, T. (1975), “Relevance: A Review of and a Framework for the Thinking on the Notion in Information Science,”Journal of the American Society for Information Science, 26, 321–343.Google Scholar
  3. vAN RIJSBERGEN, C. J. (1979),Information Retrieval Second Edition, London: Buttersworth.Google Scholar
  4. WILSON, P. (1983), “Bibliographic R & D,” inThe Study of Information, eds. F. Machlup and U. Mansfield, New York: Wiley.Google Scholar

References

  1. BENZECRI, J.-P. (1973),L'Analyse des Donnees, Tome (Volume) 2, L'Analyse des Correspondances, Paris: Dunod.Google Scholar
  2. DE LEEUW, J. (1984), “The Gifi System of Nonlinear Multivariate Analysis,” inData Analysis and Informatics 3, eds. E. Diday, M. Jambu, L. Lebart, J. Pages, and R. Tomassone, Amsterdam: North Holland, 415–424.Google Scholar
  3. ECO, U. (1983),The Name of the Rose, London: Picador.Google Scholar
  4. GABRIEL, K. R. (1978), “Least-squares Approximation of Matrices by Additive and Multiplicative Models,”Journal of the Royal Statistical Society Series B, 40, 186–196.Google Scholar
  5. GIFI, A. (1981),Nonlinear Multivariate Analysis, Leiden: Department of Data Theory.Google Scholar
  6. GOWER, J. C. (1966), “Some Distance Properties of Latent Root and Vector Methods Used in Multivariate Analysis,”Biometrika, 53, 325–338.Google Scholar
  7. GREENACRE, M. J. (1984),Theory and Applications of Correspondence Analysis, London: Academic Press.Google Scholar
  8. HASTIE, T., and TIBSHIRANI, R. (1986), “Generalized Additive Models,”Statistical Science, 1, 297–318.MathSciNetGoogle Scholar
  9. KRUSKAL, J. B. (1964), “Multidimensional Scaling by Optimizing Goodness of Fit to a Nonmetric Hypothesis,”Psychometrika, 29, 1–28.Google Scholar
  10. RAO, C.R. (1980), “Matrix Approximations and Reduction of Dimensionality in Multivariate Statistical Analysis,” inMultivariate Analysis, Volume 5, ed. P.R. Krishnaiah, Amsterdam: North Holland, 3–22.Google Scholar

References

  1. KOTELCHUCK, M., and PARKER, G. (1979),Woburn Health Data Analysis, 1969–1978, Massachusetts Department of Health.Google Scholar
  2. LAGAKOS, S. W., WESSEN, B. J., and ZELEN, M. (1986), “An Analysis of Contaminated Well Water and Health Effects in Woburn, Massachusetts,”Journal of the American Statistical Association, 81, 583–596 + discussion.Google Scholar
  3. LEGATOR, M. S., HARPER, B. L., and SCOTT, M. J. (1985),The Health Detective's Handbook: A Guide to the Investigation of Environmental Health Hazards by Nonprofessionals, Baltimore: Johns Hopkins University Press.Google Scholar
  4. PARKER, G.S., and ROSEN, S. L. (1981),Cancer Incidence and Environmental Hazards 1960–1978, Massachusetts Department of Public Health.Google Scholar

Copyright information

© Springer-Verlag 1987

Authors and Affiliations

  • Malcolm McLaren Dow
    • 1
  • Peter Willett
    • 2
  • Roderick P. McDonald
    • 3
  • Belver C. Griffith
    • 4
  • Michael Greenacre
    • 5
  • Peter G. Bryant
    • 6
  • Daniel Wartenberg
    • 7
  • Ove Frank
    • 8
  1. 1.Department of AnthropologyNorthwestern UniversityEvanstonUSA
  2. 2.Department of Information StudiesThe University of SheffieldSheffieldEngland
  3. 3.School of EducationMacquarie UniversityAustralia
  4. 4.College of Information StudiesDrexel UniversityPhiladelphiaUSA
  5. 5.Department of StatisticsUniversity of South AfricaPretoriaSouth Africa
  6. 6.College of Business and AdministrationUniversity of Colorado at DenverDenverUSA
  7. 7.Department of Environmental and Community MedicineRobert Wood Johnson Medical SchoolPiscatawayUSA
  8. 8.Department of StatisticsUniversity of StockholmStockholmSweden

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