Statistics and Computing

, Volume 3, Issue 1, pp 23–26 | Cite as

The statistical computing environment XploRe and state-of-the-art density and regression smoothing

  • M. G. Schimek
  • K. G. Schmaranz


XploRe (XploRe Systems, 1992) is a ‘computing environment for eXploratory Regression and data analysis’ more and more used in the statistical community. It is not only a highly specialized up-to-date statistics and graphics system for density and regression smoothing but also a statistical programming environment. Two versions of XploRe, 2.0 and 3.0, addressing different user groups, are available. XploRe 2.0 is menu operated, hence easier in use for exploratory data analysis. Special consideration is given to XploRe 3.0, characterized by a command-line interpreter and a macro language, called the XploRe Language. After a general description of the statistical and graphical operations as well as technical features, the extensibility of XploRe 3.0 is considered. Differences between the versions 3.0 and 2.0 are described briefly. XploRe 3.0 is compared to S-Plus 2.0, the only other matrix-oriented system for density and regression smoothing with extensibility and availability under DOS. Finally, some concluding remarks are addressed to potential users.


XploRe density and regression smoothing 


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  1. Aptech Systems Inc. (1989) The GAUSS System Version 2.0. Kent, WA.Google Scholar
  2. Breiman, L., Friedman, J., Olshen, R. and Stone, C. J. (1984) Classification and Regression Trees. Wadsworth and Brooks, Pacific Grove, CA.Google Scholar
  3. Broich, T., Härdle, W. and Krause, A. (1990) The XploRe Book. A Computing Environment for exploratory Regression and Data Analysis. Springer-Verlag, New York.Google Scholar
  4. Hastie, T. and Tibshirani, R. (1990) Generalized Additive Models. Chapman & Hall, London.Google Scholar
  5. Härdle, W. (1988) Efficient nonparametric smoothing in high dimensions using interactive graphical techniques. In: Proceedings in Computational Statistics 1988, Edwards, D. and Raun, N. E. (eds.) Physica, Heidelberg, pp. 17–30.Google Scholar
  6. Härdle, W. (1990) Applied Nonparametric Regression. Cambridge University Press, Cambridge.Google Scholar
  7. Schimek, M. G. (1991) Non-parametric regression techniques for biometric problems: Concepts and software. In Medical Informatics Europe 91, Adlassnig, K.-P., Grabner, G., Bengtsson, S. and Hansen, R. (eds.), Springer-Verlag, Berlin, pp. 562–566.Google Scholar
  8. Schimek, M. G. and Kubik, W. (1992) Möglichkeiten und Grenzen des Werkzeuges XploRe aus der Sicht des Biometrikers. In Methoden und Werkzeuge für die exploratorische Datenanalyse in den Biowissenschaften, Enke, H., Gölles, J., Haux R. and Wernecke, K.-D. (eds.), G. Fischer, Stuttgart, pp. 129–139.Google Scholar
  9. Silverman, B. W. (1986) Density Estimation for Statistics and Data Analysis. Chapman & Hall, London.Google Scholar
  10. Silverman, B. W. and Walters, G. W. (1984) BATHSPLINE. An interactive spline smoothing package. University of Bath, Bath.Google Scholar
  11. Statistical Sciences, Inc. (1991) S-Plus for DOS. Seattle, WA.Google Scholar
  12. Velleman, P. F. and Velleman, A. Y. (1988) Data Desk Professional. Statistics and reference guides. Odesta Corporation, Northbrook, IL.Google Scholar
  13. XploRe Systems (1992) XploRe — a computing environment for exploratory Regression and data analysis. Version 3.0. CORE, Louvain-la-Neuve.Google Scholar

Copyright information

© Chapman & Hall 1993

Authors and Affiliations

  • M. G. Schimek
    • 1
  • K. G. Schmaranz
    • 1
  1. 1.Medical Biometrics GroupUniversity of Graz Medical SchoolsGrazAustria

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