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Page 1 of 1 Discoveries and Discussions at useR! 2014 (UCLA) [email protected] LA-R Users (Meetup) Group Thursday, September 4, 2014 Santa Monica, CA This document is available at: 1. Some new R Books (I’ve brought a few with me today): Cotton, R. (2013), Learning R, O’Reilly. Kolaczyk, E, at al. (2014), Statistical Analysis of Network Data with R, Springer. Jockers, M. (2014), Text Analysis with R for Students of Literature, Springer. Pollock, P. (2014), An R Companion to Political Analysis, Sage. 2. R Packages of note: T. Hesterberg (Google) resample; S. Urbanek (AT&T) rJava; D. Mimno (Cornell) mallet; C. Signorino et al. (U. of Rochester) games; Rstudio dplyr; ggvis; 3. Conference Posters I especially liked: S. Kovalchik (RAND) (tennis data/stats); M. Jimichi, et al. (Kwansei Gakuin U.) (ggplot2/ggviz of Nikkei stock market); S. Porter (Added Value) (RExcel via Windows COM); E. Cramer, el al. (Scripps) (R w/ 60 cores and 120 concurrent threads); M. Çetikaya- Rundel (Duke) (knitr/Rmarkdown for elem. stat. non-majors); S. Griffith (Cleveland Clinic) (ggplot2, shiny, github/shinyIncubator viz. apps by and for HS AP stat. students) 4. New Open Educational Resources (OER) for introductory statistics D. Diez et al. Two books: classical (frequentist), contemporary (resample/simulation) Authors: a bunch of CCC faculty Target audience: H.S. AP stat (so no R…yet; still w/ TI-calculators) 5. Discussions regarding Julia (many MIT and Stanford committers) a. Orthogonal (mostly) to R; replacement (mostly) for MATLAB; complement (again, mostly) for NumPy; extends (mostly) C/Fortran Presentations from JuliaCon 2014 (June) are now up on the site. See: Applied Math/Industrial Engineering folks are early-adopters—MIPs, FFT, NLP, etc. Optimization/Resource Allocation problems, not necessarily Predictive Modeling.