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Statistical Modeling

  • Andreas Krause
  • Melvin Olson
Part of the Statistics and Computing book series (SCO)

Abstract

We have now learned some elementary statistical techniques in S-Plus and the basics of graphical data analysis. The next step is to see what S-Plus has to offer in terms of modeling. Statistical modeling is one of the strongest S-Plus features because of its unified approach, wide variety of model types, and excellent diagnostic capabilities. We start with an example of how to fit a simple linear regression model and corresponding diagnostics. The example is presented with a minimum of technical explanation, designed as a quick introduction. We then formally explain the unified approach to model syntax and structure, along with comments on several of the more popular types of statistical models.

Keywords

Data Frame Simple Linear Regression Model Regression Tree Model 75th Quantile Summary Function 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media New York 1997

Authors and Affiliations

  • Andreas Krause
    • 1
  • Melvin Olson
    • 2
  1. 1.GeneData AGBaselSwitzerland
  2. 2.Ares-SeronoGeneva 20Switzerland

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