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The History of Compstat and Key- Steps of Statistical Computing During the Last 30 Years

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COMPSTAT 2004 — Proceedings in Computational Statistics

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Abstract

First of all we try to trace the situation and the ideas that culminated in the first COMPSTAT symposium in the year 1974 held at the University of Vienna, Austria. Special emphasis is given to the memories of our founding member P. P. Sint who had been the driving force behind early COMPSTAT and had served it for twenty years.

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References

  1. Bruckmann, G., Ferschl, F. and Schmetterer, L. (1974, eds.). COMPSTAT 1974. Proceedings in Computational Statistics. Physica-Verlag, Wien.

    MATH  Google Scholar 

  2. Gordesch, J. and Naeve, P. (1976, eds.). COMPSTAT 1976. Proceedings in Computational Statistics. 2nd Symposium Berlin/FRG. PhysicaVerlag, Wien.

    Google Scholar 

  3. Corsten, L. C. A. and Hermans, J. (1978, eds.). COMPSTAT 1978. Proceedings in Computational Statistics. 3rd Symposium Leiden/The Netherlands. Physica-Verlag, Wien.

    Google Scholar 

  4. Barritt, M. M. and Wishart, D. (1980, eds.). COMPSTAT 1980. Proceedings in Computational Statistics. 4th Symposium Edinburgh/UK. Physica-Verlag, Wien.

    Google Scholar 

  5. Caussinus, H., Ettinger, P. and Tamassone, R. (1982, eds.). COMPSTAT 1982. Proceedings in Computational Statistics. 5th Symposium Toulouse/France. Physica-Verlag, Wien.

    Google Scholar 

  6. Havránek, T., Šidák, Z. and Novák, M. (1984, eds.).COMPSTAT 1984. Proceedings in Computational Statistics. 6th Symposium Prague/CSSR. Physica-Verlag, Wien.

    Google Scholar 

  7. De Antoni, F., Lauro, N. and Rizzi, A. (1986, eds.). COMPSTAT 1986. Proceedings in Computational Statistics. 7th Symposium Rome/Italy. Physica-Verlag, Wien.

    Google Scholar 

  8. Edwards, D. and Raun, N. E. (1988, eds.). COMPSTAT 1988. Proceedings in Computational Statistics. 8th Symposium Copenhagen/Denmark. Physica-Verlag, Heidelberg.

    Google Scholar 

  9. Momirović, K. and Mildner, V. (1990, eds.). COMPSTAT 1990. Proceedings in Computational Statistics. 9th Symposium Dubrovnik/Yugoslavia. Physica-Verlag, Heidelberg.

    Google Scholar 

  10. Dodge, Y. and Whittaker, J. (1992, eds.). Computational Statistics. Volume 1 and 2. Proceedings of the 10th Symposium, COMPSTAT, Neuchâtel/ &’Switzerland. Physica-Verlag, Heidelberg.

    Google Scholar 

  11. Dutter, W. and Grossmann, W. (1994, eds.). COMPSTAT 1994. Proceedings in Computational Statistics. 11th Symposium Vienna/Austria. Physica-Verlag, Heidelberg.

    Google Scholar 

  12. Härdie, W. and Schimek, M. G. (1996, eds.) Statistical Theory and Computational Aspects of Smoothing. Proceedings of the COMPSTAT &’ 94 Satellite Meeting held in Semmering, Austria, 27-28 August 1994, Physica-Verlag, Heidelberg.

    Google Scholar 

  13. Prat, A. (1996, ed.). COMPSTAT 1996. Proceedings in Computational Statistics. 12th Symposium Barcelona/Spain. Physica-Verlag, Heidelberg.

    MATH  Google Scholar 

  14. Payne, R. and Green, P. (1998, eds.). COMPSTAT 1998. Proceedings in Computational Statistics. 13th Symposium Bristol/UK. Physica-Verlag, Heidelberg.

    Google Scholar 

  15. Bethlehem, J. G. and van der Heijden, P. G. M. (2000, eds.). COMPSTAT 2000. Proceedings in Computational Statistics. 14th Symposium Utrecht/The Netherlands. Physica-Verlag, Heidelberg.

    Google Scholar 

  16. Härdie, W. and Rönz, B. (2002, eds.). COMPSTAT 2002. Proceedings in Computational Statistics. 15th Symposium Berlin/Germany. PhysicaVerlag, Heidelberg.

    Google Scholar 

  17. ACM (1999). Software Systems Award. Press Release. New York, March 23, 1999. http://www.acm.org/announcements/ss99.html.

  18. Adam, A. (1973). Von himmlischen Uhrwerk zur statistischen Fabrik. 600 Jahre Entdeckungsreise in das Neulandösterreischer Statistik und Datenverarbeitung. Munk, Wien.

    Google Scholar 

  19. Anscombe, F. (1981). Computing in Statistical Science through APL. Springer-Verlag, New York.

    Book  MATH  Google Scholar 

  20. Andrews, D. F., Bickel, P. J., Hampel, F. R., Huber, P. J., Rogers, W. H. and Tukey, J. W. (1972). Robust Estimation of Location: Survey and Advances. Princeton University Press, Princeton/NJ.

    Google Scholar 

  21. Breiman, L., Friedman, J. H., Olshen, R. A. and Stone, C. J. (1984). Classification and Regression Trees. Wadsworth, Pacific Grove/CA.

    MATH  Google Scholar 

  22. Buja, A., Hastie, T. and Tibshirani, R. (1989). Linear smoothers and additive models (with discussion), Ann. Statist., 17, 453–555.

    Article  MATH  MathSciNet  Google Scholar 

  23. Chambers, J. M. (1998). Programming with Data-A Guide to the S Language. Springer-Verlag, New York.

    Book  MATH  Google Scholar 

  24. Chambers, J. M. and Hastie, T. J. (1992). Statistical Models in S. Chapman & Hall, London.

    MATH  Google Scholar 

  25. Christeller, S., Meystre, A., Ballmer, U. and Glutz, G. (1974). SAS. A Software System for Statistical Data Analysis. In Bruckmann, G., Ferschl, F. and Schmetterer, L. (eds.). COMPSTAT. Proceedings in Computational Statistics, 479–488.

    Google Scholar 

  26. Codd, E. F. (1970). A Relational Model for Large Shared Data Banks. CACM, 13, 377–387.

    Article  MATH  Google Scholar 

  27. Coppi, R. (2002). A Theoretical Framework for Data Mining: the Informational Paradigm. Computat. Statist. Data Anal., 38, 501–515.

    Article  MATH  MathSciNet  Google Scholar 

  28. Cox, D. J. (1972). Regression models and life-tables (with discussion). J. Royal Statist. Soc., B 34, 187–220.

    Google Scholar 

  29. Dahl, O. R. and Nygaard, K. (1966). Simula — an Algol-based Simulation Language. CACM, 9, 671–678.

    Article  MATH  Google Scholar 

  30. Dempster, A. P., Laird, N. and Rubin, D. B. (1977). Maximum likelihood from incomplete data via the EM algorithm (with discussion). J. Royal Statist. Soc, B 39, 1–38.

    MathSciNet  Google Scholar 

  31. Devroye, L. (1986). Non-Uniform Random Variate Generation. Springer-Verlag, New York.

    Book  MATH  Google Scholar 

  32. Dirschedl, P. and Ostermann, R. (1994, eds.). Computational Statistics. Physica-Verlag, Heidelberg.

    Book  MATH  Google Scholar 

  33. Dixon, W. J. (1971, ed.). BMD. Biomedical Computer Programs. University of California Press, Los Angeles/CA.

    Google Scholar 

  34. Dodge, Y. and Whittaker, J. (1992). In Dodge, Y. and Whittaker, J. (eds.) Science, Data, Statistics and Computing. In Computational Statistics. Volume 1, 3–7.

    Google Scholar 

  35. Efron, B. (1979). Bootstrap methods: another look at the jackknife. Ann. Statist., 7, 1–26.

    Article  MATH  MathSciNet  Google Scholar 

  36. Efron, B. (2002). Statistics in the 20th Century and the 21th. In Dutter, R. (ed.) Festschrift 50 JahreÖsterreichische Statistische Gesellschaft 1951–2001. Austrian Statistical Society, Vienna, 7–20.

    Google Scholar 

  37. Efron, B. (2003). Robbins, empirical Bayes and microarrays. Ann. Statist., 31, 366–378.

    Article  MATH  MathSciNet  Google Scholar 

  38. Fisherkeller, M. A., Friedman, J. H. and Tukey, J. W. T. (1974). PRIM-9. An Interactive Multidimensional Data Display System. Stanford Linear Accelerator Publication No. 1408. Palo Alto/CA.

    Google Scholar 

  39. Fleck, C. (2000). Wie Neues nicht entsteht. Die Gründung des Instituts für Höhere Studien in Wien durch Ex-Österreicher und die Ford Foundation. Österreichische Zeitschrift für Geschichtswissenschaften, 1, 129–177.

    Google Scholar 

  40. Francis, I. (1981). Statistical Software. A Comparative Review. North Holland, New York.

    Google Scholar 

  41. Frawley, W., Piatetsky-Shapiro, G. and Matheus, C.(1992). Knowledge Discovery in Databases: An Overview. AI Magazine, Fall 1992, 213–228.

    Google Scholar 

  42. Friedman, J. H. and Stuetzle, W. (2002). John W. Tukey’s work on interactive graphics. Ann. Statist., 30, 1629–1639.

    Article  MATH  MathSciNet  Google Scholar 

  43. Friedman, J. H. and Tukey, J. W. (1974). A projection pursuit algorithm for exploratory data analysis. IEEE Trans. Comp., C 23, 881–890.

    Article  Google Scholar 

  44. Gelman, A., Carlin, J. B., Stern, H. S. and Rubin, D. B. (1996). Bayesian Data Analysis. Chapman &Hall, London.

    Google Scholar 

  45. Geman, S. and Geman, D. (1984). Stochastic relaxation, Gibbs distributions, and the Bayesian restoration of images. IEEE Trans. Pattern Anal. Machine Intellig., 6, 721–741.

    Article  MATH  Google Scholar 

  46. Gentle, J. E. (2002). Elements of Computational Statistics. Springer-Verlag, New York.

    MATH  Google Scholar 

  47. Gershenfeld, N. (1999). The Nature of Mathematical Modeling. Cambridge University Press, Cambridge/UK.

    MATH  Google Scholar 

  48. Goldstine, H. H. (1972). The Computer from Pascal to von Neumann. Princeton University Press, Princeton/NJ.

    MATH  Google Scholar 

  49. Hand, D. (1996). Classification and Computers, Shifting the Focus. In Prat, A. (ed.) COMPSTAT 1996. Proceedings in Computational Statistics., 77–88.

    Google Scholar 

  50. Hastie, T. and Tibshirani, R. (1990). Generalized Additive Models. Chapman & Hall, London.

    MATH  Google Scholar 

  51. Hastie, T., Tibshirani, R. and Friedman, J. (2001). The Elements of Statistical Learning. Springer-Verlag, New York.

    Book  MATH  Google Scholar 

  52. Hastings, W. K. (1970). Monte Carlo sampling methods using Markov chains and their applications. Biometrika, 57, 97–109.

    Article  MATH  Google Scholar 

  53. Härdie, W., Klinke, S. and Turlach, B. A. (1995). Xplo Re: An Interactive Statistical Computing Environment. Springer-Verlag, New York.

    Book  Google Scholar 

  54. Heide, L. (2003). Diffusing the emerging punched card technology in Europe 1889-1914. Information Systems and Technology in Organizations and Society. ISTOS-Workshop Universitat Pompeu Fabra, Barcelona, http://cbs.dk/staff/lars.heide/ISTOS/paper-10.pdf.

  55. Hornik, K. and Leisch, F. (2002). Vienna and R: Love, Marriage and the Future. In Dutter, R. (ed.) Festschrift 50 Jahre Österreichische Statistische Gesellschaft 1951-2001, Austrian Statistical Society, 61–70.

    Google Scholar 

  56. Huber, P. J. (1964). Robust estimation of a location parameter, Ann. Math. Statist., 35, 73–101.

    Article  MATH  MathSciNet  Google Scholar 

  57. Huber, P. J. (1994). Huge Datasets. In Dutter, W. and Grossmann, W. (eds.) COMPSTAT 1994-Proceedings in Computational Statistics, 1–13.

    Google Scholar 

  58. Huber, P. J. (1999). Massive Dataset Workshop: Four Years After, J. Computat. Graph. Statist., 8, 635–652.

    Google Scholar 

  59. Ihaka, R. and Gentleman, R. (1996). R: A language for data analysis and graphics. J. Computat. Graph. Statist., 5, 299–314.

    Google Scholar 

  60. Lauritzen, S. L. and Wermuth, N. (1989). Graphical models for association between variables, some of which are qualitative and some quantitative. J. Royal Statist. Soc., B 50, 157–224.

    Google Scholar 

  61. Lauro, C. (1996). Computational Statistics or Statistical Computing, is that the question? Computat. Statist. Data Anal., 23, 191–193.

    Article  Google Scholar 

  62. Mehta, C. R. and Patel, N. R. (1992). Exact Logistic Regression: Theory, Applications, Software. In Dodge, Y and Whittacker, J. (eds.) Computational Statistics. Volume 2, 63–78.

    Google Scholar 

  63. Mehta, C. R. and Patel, N. R. (1997). Exact Inference for Categorical Data. Electronic Publication: Harvard University and Cytel Software Corporation, http: www.cytel/Library/articles.asp.

  64. Mehta, C. R., Patel, N. R. and Senchaudhuri, P. (2000). Efficient Monte Carlo Methods for Conditional Logistic Regression. J. Amer. Statist. Assoc., 95, 99–108.

    Article  Google Scholar 

  65. Metropolis, N. and Ulam, S. (1949). The Monte Carlo Method. J. Amer. Statist. Assoc, 44, 335–342.

    Article  MATH  MathSciNet  Google Scholar 

  66. Meyer, D. Leisch, F., Hothorn, T. and Hornik, K. (2002). StatDataML: An XML Format for Statistical Data. In Härdie, W. and Rönz, B. (eds.)COMPSTAT 2002. Proceedings in Computational Statistics., 545–550.

    Google Scholar 

  67. Monahan, J. F. (2001). Numerical Methods of Statistics. Cambridge University Press, Cambridge/UK.

    Book  MATH  Google Scholar 

  68. Neider, J. A. (1974). Genstat-A Statistical System. In Bruckmann, G., Ferschl, F. and Schmetterer, L. (eds.) COMPSTAT. Proceedings in Computational Statistics, 499–506.

    Google Scholar 

  69. Neider, J. A. (1978). The Future of Statistical Software. In Corsten, L. C. A. and Hermans, J. (eds.) COMPSTAT 1978. Proceedings in Computational Statistics, 11–19.

    Google Scholar 

  70. Neider, J. A. and Wedderburn, R. W. M. (1972). Generalized linear models. J. Royal Statist. Soc., A 135, 370–84.

    Google Scholar 

  71. Neuwirth, E. and Baier, T. (2002). Embedding R in standard software, and the other way round. In Hornik, K. and Leisch, F. (eds.) DSC 2001 Proceedings. 2nd International Workshop on Distributed Statistical Computing, http://www.ci.tuwien.ac.at/Conferences/DSC-2001.

  72. Owen, D. B. (1976). On the history of statistics and probability. Proceedings of a symposium on the American mathematical heritage. Dekker, New York.

    MATH  Google Scholar 

  73. Ripley, B. D. (1987). Stochastic Simulation. Wiley, New York.

    Book  MATH  Google Scholar 

  74. Robbins, H. (1956). An empirical Bayes Approach to Statistics. Proc. Third Berkeley Symp. Statist. Probab., 1, 157–163.

    MathSciNet  Google Scholar 

  75. Schäffler, O. (1895). Neuerungen an statistischen Zählmaschinen. & Österreichisches Patentprivileg No.46/3182, Patentarchiv, Wien.

    Google Scholar 

  76. Shoshani, A. (1997). OLAP and Statistical Databases: Similarities and Differences. Proceedings 16th ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems 1997, 185–196.

    Google Scholar 

  77. Stone, C. (1977). Consistent nonparametric regression (with discussion). Ann. Statist., 5, 595–645.

    Article  MATH  MathSciNet  Google Scholar 

  78. Sundgren, B. (1975). Theory of Data Bases. Petrocelli/Charter, New York.

    Google Scholar 

  79. Temple Lang, D. (2000). The Omegahat Environment: New Possibilities for Statistical Computing. J. Computat. Graph. Statist., 9, 423–451.

    MathSciNet  Google Scholar 

  80. Thisted, R. A. (1988). Elements of Statistical Computing. Chapman & Hall, New York.

    MATH  Google Scholar 

  81. Tierney, L. (1989). XLISP-STAT: A Statistical Environment Based on the XLISP Language, Technical Report No. 528, School of Statistics, University of Minnesota, http://www.stat.umn.edu/luke/xls/tutorial/techreport/techreport.html.

  82. Tierney, L. (1990). LISP-STAT: An Object-Oriented Environment for Statistical Computing and Dynamic Graphics. Wiley, New York.

    Book  MATH  Google Scholar 

  83. Tukey, J. W. (1962). The future of data analysis. Ann. Math. Statist., 33, 1–67 and 812.

    Article  MATH  MathSciNet  Google Scholar 

  84. Tukey, J. W. (1970). Exploratory Data Analysis. Volume I and II (limited preliminary edition). Addison-Wesley, Reading/MA.

    Google Scholar 

  85. Tukey, J. W. and Cooley, J. W. (1965). An algorithm for the machine calculation of complex Fourier series. Math. Comput., 19, 237–301.

    MathSciNet  Google Scholar 

  86. Wegman, E. J. and Marchette, D. J (2003). On Some Techniques for Streaming Data: A Case Study of Internet Packet Headers. J. Computat. Graph. Statist., 12, 893–914.

    Article  MathSciNet  Google Scholar 

  87. Wilkinson, L., Rope, D. J., Carr, D. B. and Rubin, M. A. (2000). The Language of Graphics. J. Computat. Graph. Statist., 9, 558–581.

    MathSciNet  Google Scholar 

  88. Zemanek, H. (1975). Otto Schäffler. Ein vergessener & Österreicher. Die Biographie eines genialen Unternehmers und Erfinders. & #x00D6;sterreichischer Gewerbeverein. Jahrbuch, 92, 71–92.

    Google Scholar 

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Author information

Authors and Affiliations

  1. Institute for Statistics and Decision Support Systems, University of Vienna, Universitätsstraße 5, A-1010, Wien, Austria

    Wilfried Grossmann

  2. Institute for Medical Informatics, Statistics and Documentation, Medical University of Graz, Auenbruggerplatz 2, A-8036, Graz, Austria

    Michael G. Schimek

  3. Institute for European Integration Research, Austrian Academy of Sciences, Prinz Eugen Straße 8-10/2, A-1040, Wien, Austria

    Peter Paul Sint

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  1. Wilfried Grossmann
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  2. Michael G. Schimek
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Editors and Affiliations

  1. Faculty of Mathematics and Physics Department of Statistics and Probability, Charles University, Sokolovská 83, 18675, Prague 8 - Karlin, Czech Republic

    Jaromir Antoch

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Grossmann, W., Schimek, M.G., Sint, P.P. (2004). The History of Compstat and Key- Steps of Statistical Computing During the Last 30 Years. In: Antoch, J. (eds) COMPSTAT 2004 — Proceedings in Computational Statistics. Physica, Heidelberg. https://doi.org/10.1007/978-3-7908-2656-2_1

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  • DOI: https://doi.org/10.1007/978-3-7908-2656-2_1

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  • Print ISBN: 978-3-7908-1554-2

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