Discriminant function steroids

In the next edition of this blog, I will return to looking at R’s plotting capabilities with a focus on the ggplot2 package. In the meantime, enjoy using the apply function and all it has to offer. Related Share Tweet To leave a comment for the author, please follow the link and comment on their blog: Musings of a forgetful functor . R- offers daily e-mail updates about R news and tutorials on topics such as: Data science , Big Data, R jobs , visualization ( ggplot2 , Boxplots , maps , animation ), programming ( RStudio , Sweave , LaTeX , SQL , Eclipse , git , hadoop , Web Scraping ) statistics ( regression , PCA , time series , trading ) and more...

Discriminant function analysis is very similar to logistic regression , and both can be used to answer the same research questions. [2] Logistic regression does not have as many assumptions and restrictions as discriminant analysis. However, when discriminant analysis’ assumptions are met, it is more powerful than logistic regression. [ citation needed ] Unlike logistic regression, discriminant analysis can be used with small sample sizes. It has been shown that when sample sizes are equal, and homogeneity of variance/covariance holds, discriminant analysis is more accurate. [3] With all this being considered, logistic regression has become the common choice, since the assumptions of discriminant analysis are rarely met. [1] [3]

Discriminant function steroids

discriminant function steroids

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