Hi Ryan, Sorry for the late reply.
The slides you are thinking about are from a talk I gave at Columbia back in 2008, so they are a bit outdated. http://www.quantmod.com/Columbia2008/ColumbiaDec4.pdf In general, xts has gotten substantially faster since then. Some things in xts are now even faster than using raw matrices for data. x <- .xts(1:1e6L, 1:1e6L) system.time( x[,1] ) user system elapsed 0.002 0.000 0.002 m <- coredata(x) # a matrix, no 'time' index, so not really a time series system.time( m[,1] ) user system elapsed 0.015 0.000 0.015 I haven't put together a comparison in a while, but repeating the benchmarks in the slides have xts with a substantial edge, often times an order of magnitude better (even 2 or 3 orders of magnitude) Most of the differences in xts vs. zoo come from the C in xts of course. But as Gabor noted, the effort is under way to move many of the core C functions back up into zoo. The limits here are that while xts and zoo are very, very compatible - some xts functionality differs - and we can't realistically break anything in zoo in the process. The other limit is with respect to time. Some of the code is in zoo already, though not 'switched on' yet. Subsetting and basic Ops are really the primary target for the migration. My 2c is that xts is as fast as it can be, as it is all highly optimized C --- 10x faster than all the other ts classes at a minimum --- but that zoo will be brought up to speed "soon". ;-) The other part of xts is that it does make "development" speedier by way of the ISO8601 subsetting and related to.period aggregation code. Not sure if that counts for 'performance speed' as your original post requests though. Best, Jeff P.S. The timeSeries values in the slides are _much_ improved as of current implementations - though still much slower than xts. On Wed, Jan 19, 2011 at 7:08 AM, Sheftel, Ryan <[email protected]> wrote: > > I am looking for a comparison of the performance speed between xts and > zoo on time series. I remember once seeing this in a pdf document, > perhaps a magazine article?, but after extensive google-ing I have come > up blank. > > Any direction would be helpful before I reproduce the results myself. > Thanks. > > =============================================================================== > Please access the attached hyperlink for an important el...{{dropped:8}} > > _______________________________________________ > [email protected] mailing list > https://stat.ethz.ch/mailman/listinfo/r-sig-finance > -- Subscriber-posting only. If you want to post, subscribe first. > -- Also note that this is not the r-help list where general R questions > should go. > -- Jeffrey Ryan [email protected] www.lemnica.com _______________________________________________ [email protected] mailing list https://stat.ethz.ch/mailman/listinfo/r-sig-finance -- Subscriber-posting only. If you want to post, subscribe first. -- Also note that this is not the r-help list where general R questions should go.
