Statistical Models in S (Chapman & Hall Computer Science Series)

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Statistical Models in S extends the S language to fit and analyze a variety of statistical models, including analysis of variance, generalized linear models, additive models, local regression, and tree-based models. The contributions of the ten authors-most of whom work in the statistics research department at AT&T Bell Laboratories-represent results of research in both the computational and statistical aspects of modeling data.

Author(s): John M. Chambers
Edition: 1
Year: 1991

Language: English
Pages: 500