Now that you've got a good sense of how to 'speak' R, let's use it with linear regression to make distinctive predictions.

R is a free computing and graphical software/environment for statistical analysis. Part III of this short course consists of 3 sections: Section 5 introduces the concept of generalized linear models.

Parametric versus Semi/nonparametric Regression Models Course Topics Linear models, generalized linear models, and nonlinear models are examples of parametric regression models because we know the ...

Previous published work deals with goodness of fit tests of the generalized linear model against zero-inflation and against over-dispersion separately. In this paper we deal with the class of ...

Among others, Fan and Lv [J. R. Stat. Soc. Ser. B Stat. Methodol. 70 (2008) 849—911] propose an independent screening framework by ranking the marginal correlations. They showed that the correlation ...