In case you missed them, here are some articles from September of particular interest to R users.

A tutorial on using R with Jupyter Notebooks and how to control the size of R graphics therein.

A new version of Revolution R Open is available, featuring multi-threaded computing for R 3.2.2.

One benefit of fitting statistical models to large data sets: learning curves.

Using the AzureML package to publish R functions as web services.

The R Consortium forms a committee to oversee projects, headed by Hadley Wickham.

Functions for interpolation in R.

The EARL London conference (preview here) included many applications of R, from AstraZeneca, Allstate, Douwe Egberts coffee and others.

A new online Data Science and Machine Learning course, featuring R and sponsored by Microsoft.

Reading financial time series data into R with the zoo package.

An update to the checkpoint package brings support for knitr and rmarkdown documents in reproducible projects.

The new Microsoft Data Science User Group Program offers sponsorships for R user groups worldwide.

A series on model validation in R using: basic methods; in-training set measures; out-of-sample procedures; and cross-validation techniques.

BlueSky Statistics, a new open-source GUI for R.

Accessing data in Google spreadsheets with the googlesheets package for R.

Antony Unwin on the care of datasets in R packages.

General interest stories (not related to R) in the past month included: building a scale model of the solar system, a new way to visualize the Discrete Fourier Transform, and a Portal-themed remodel.

As always, thanks for the comments and please send any suggestions to me at david@revolutionanalytics.com. Don't forget you can follow the blog using an RSS reader, via email using blogtrottr, or by following me on Twitter (I'm @revodavid). You can find roundups of previous months here.