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Pakket: r-cran-design (2.3-0-2)

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GNU R regression modeling strategies tools by Frank Harrell

Regression modeling, testing, estimation, validation, graphics, prediction, and typesetting by storing enhanced model design attributes in the fit. Design is a collection of about 180 functions that assist and streamline modeling, especially for biostatistical and epidemiologic applications. It also contains new functions for binary and ordinal logistic regression models and the Buckley-James multiple regression model for right-censored responses, and implements penalized maximum likelihood estimation for logistic and ordinary linear models. Design works with almost any regression model, but it was especially written to work with logistic regression, Cox regression, accelerated failure time models, ordinary linear models, and the Buckley-James model.

See Frank Harrell (2002), Regression Modeling Strategies, Springer Series in Statistics, as well as http://biostat.mc.vanderbilt.edu/rms and http://biostat.mc.vanderbilt.edu/s/Design.

Tags: Softwareontwikkeling: Ontwikkelen in GNU R, Bibliotheken, Field: Statistics, Implemented in: GNU R, Role: Application Data, Application Suite: GNU

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