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.
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© 2000 Springer-Verlag New York, Inc.
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(2000). Statistical Modeling. In: The Basics of S and S-Plus. Statistics and Computing. Springer, New York, NY. https://doi.org/10.1007/978-0-387-22709-2_8
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DOI: https://doi.org/10.1007/978-0-387-22709-2_8
Publisher Name: Springer, New York, NY
Print ISBN: 978-0-387-98961-7
Online ISBN: 978-0-387-22709-2
eBook Packages: Springer Book Archive