Dealing with Correlated High-Dimensional Data

October 10, 2017
By

(This article was first published on Computational Social Science, and kindly contributed to R-bloggers)

[unable to retrieve full-text content]

Theory to Application 1 I recently realized my review of Michael Alvarez’s edited volume Computational Social Science: Discovery and Prediction went online a while ago. If memory serves, used to be the case that book reviews were freely available; alas now even a 400-word long piece is behind a paywall. I initially planned to do a post covering the whole book—at least the application part, as the volume is neatly segregated on theory vs.

To leave a comment for the author, please follow the link and comment on their blog: Computational Social Science.

R-bloggers.com 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...



If you got this far, why not subscribe for updates from the site? Choose your flavor: e-mail, twitter, RSS, or facebook...

Comments are closed.

Search R-bloggers

Sponsors

Never miss an update!
Subscribe to R-bloggers to receive
e-mails with the latest R posts.
(You will not see this message again.)

Click here to close (This popup will not appear again)