# xts and GSOC 2012

**tradeblotter » R**, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)

Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.

Josh Ulrich and Jeff Ryan mentored a Google Summer of Code (GSOC) project this summer focused on experimental functionality for xts in collaboration with R. Michael Weylandt, a student in operations research and financial engineering from Princeton. You might recognize Michael from his presentation at R/Finance this year, where he gave a talk entitled “A Short Introduction to Real-Time Portfolio/Market Monitoring with R“.

There were three main objectives of this GSOC project. One was to extend the plotting functionality of xts – to replace the existing plot.xts function with something much more generally useful and to add a barchart.xts primitive that handles stacked bars for time series with negative values. The proof of concept for both of these graphics come from chart functions in PerformanceAnalytics, but a variety of other improvements were also discussed.

Another objective was to experiment with supporting multiple data types within the same object for time series. The concept here is something like a data.frame, which allows class-specific list elements, aligned on an index. Michael wrote a prototype and definitely moved the ball forward here. Fuller functionality will require more test cases to be written to validate the approach and flush out bugs, as well as to add a number of utility functions such as rbind, cbind, etc.

The third objective was to provide ‘bridge’ functionality to convert xts objects to methods that assume a regular time series, such as AR/ARIMA, Holt Winters, or VAR methods, using something like the the zooreg subclass and some translations. Michael provides a number of these for arima, acf, pacf, HoltWinters, and others. These are convenience wrappers for xts users that manage the xts data into the underlying functions, then as appropriate with the results (such as residuals in the case of arima) are coerced back to xts objects.

The result is contained in a supplementary package called xtsExtra, which Michael constructed as a side-pocket for newly developed functionality, any or all of which may end up in the xts package at some point. Beyond Jeff and Josh, Michael opened up to the broader r-sig-finance community to get feedback on xtsExtra, which resulted in several helpful conversations with Jonathan Cornelison, Eric Zivot, Rob Hyndman, Stuart Greenlee, Kenton Russell, Brian Peterson and me.

I want to step back to the first objective for a moment to talk for a moment about `plot.xts`

. klr at TimelyPortfolio immediately took to the code and exercised it well – here is a particularly good chart. Here’s another. And another. Oh, and this one! These were great examples, and I think they are suggestive of how the function could be extended even further, perhaps simplifying the interface and extending the panel functionality. That might require some significant re-work, but I think the results will be well worth it. I think Jeff Ryan might have some tricks up his sleeve as well…

We’ll see where some of this speculation goes, but I want **to thank Michael again for his commendable efforts this summer!** His has been a considerable effort to extend and improve xts in some very useful ways, and I’m looking forward to his continued involvement in this and perhaps other endevors.

**leave a comment**for the author, please follow the link and comment on their blog:

**tradeblotter » R**.

R-bloggers.com offers

**daily e-mail updates**about R news and tutorials about learning R and many other topics. Click here if you're looking to post or find an R/data-science job.

Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.