Learn about the cumsum function in R for running totals

By popular demand, we've made the video of our 30-minute webcast "The R Project" available on YouTube so that everyone can easily watch it. If you (or a friend!) have ever wondered what this R thing is all about, this is the video for you. Here's the first part: Because of YouTube restrictions it's split up into four parts,...

Over at Cerebral Mastication, JD Long tells a characteristically entertaining and informative story about how he uses R to run stochastic simulations of insurance portfolios and reinsurance treaties. A typical job involves 10,000 simulations, and when each estimate takes over 20 seconds you're talking some serious time to get the job done. Fortunately, this is the kind of problem...

This RClimate Script lets users retrieve and plot the latest data on Arctic Sea Ice Extent trends by month from 1979 to latest completed month. The trend chart shows National Snow and Ice Data Center’s (NSIDC) monthly Arctic Sea Ice extent data. Arctic Sea Ice Trend by Month I’ve discussed the Arctic sea ice extent

Update Friday, May 14, 2010: See this newer post on LocusZoom. If you caught Cristen Willer's seminar here a few weeks ago you saw several beautiful figures in the style of a manhattan plot, but zoomed in around a region of interest, with several ot...

Dear Readers,Today I would like to post the easy way of determining number of lines/records in any given large file using R.Directly to point.1) If data set is small let say less than 50MB or around in R one can read it with ease using: length(readLines("xyzfile.csv"))2) But if data set is too large say more...

Dear Readers,Today I would like to post the easy way of determining number of lines/records in any given large file using R.Directly to point.1) If data set is small let say less than 50MB or around in R one can read it with ease using: length(readLines("xyzfile.csv"))2) But if data set is too large say more...

If you're using regression models but want really hone your regression-fu this short course on Regression Modeling Strategies by Frank Harrell looks really interesting. Frank is the author of the book Regression Modeling Strategies which is my go-to reference whenever I'm doing regression of any kind in R, so it's definitely worth a trip to Nashville to if you...

One of my primary uses for R is to build stochastic simulations of insurance portfolios and reinsurance treaties. It’s not uncommon for each of my simulations to take 20 seconds or more to complete (if you’re doing the math, that’s 55 hours for 10K sims or, approximately 453 games of solitaire) . Initially I ran

A special double edition of the Package Update Roundup this month! This is a list of new or updated packages that were released for R in December and January, as announced on the r-packages mailing list. To include other updates on this list, please email David Smith. For a complete list of all updates on CRAN, see the CRANberries...

Lately I have been using a lot of Python for signal processing and I quite like SciPy. However, I have been missing something like Sweave, which is great literate programming environment for R. Today I managed to look a bit more into it and found this hack on how to use Python code in Sweave

pre{ border: 1px solid black; font-size: x-small ; } Dirk released Rcpp 0.7.5 yesterday The main thing is the smarter wrap function that now uses techniques of type traits and template meta-programming to have a compile time guess at whether a...

A new release of our Rcpp R / C++ interface classes is now out, the version number is 0.7.5. It comes on the heels of the release 0.7.4 and keeps with our semi-frantic schedule of releases every ten or so days going. The package is now on CRAN and Debi...

A new release of our Rcpp R / C++ interface classes is now out, the version number is 0.7.5. It comes on the heels of the release 0.7.4 and keeps with our semi-frantic schedule of releases every ten or so days going. The package is now on CRAN and Deb...

This tutorial covers profiling of Linux servers using open-source tools such as "iostat", "oprofile" and "blktrace". Both processor-bound and I/O-bound cases are covered, and the emphasis is on tools that provide visual displays of relevant metrics. Li...

Presentation given by John Myles White on February 4, 2010 to the NYC R Statistical Meetup. During that talk John covers several techniques for performing spatial analytics in R.

Table of contents Modifications to the custom driver: Example usage Lately I have been using a lot of Python for signal processing and I quite like SciPy. However, I have been missing something like Sweave, which is great literate programming environment for R. Today I managed to look a bit more into it and found this hack on how...

Table of contents Modifications to the custom driver: Example usage Lately I have been using a lot of Python for signal processing and I quite like SciPy. However, I have been missing something like Sweave, which is great literate programming environment for R. Today I managed to look a bit more into it and found this hack on how...

The video from John Myles White’s outstanding introductory talk on spatial analysis with R to the NYC R Statistical Meetup is now available in the R video repository, and is also embedded after the jump. I would like to thank John for this fantastic talk, and for those interested the slides from this talk have also been

Registrations are now open for the R/Finance 2010 conference, to be help April 16-17 in Chicago. Last year's meeting was a great success, and this year's looks to be just as good, with some great keynotes lined up: Analysis of Integrated and Co-integrated Time Series with R (Bernhard Pfaff) Leverage Space Portfolio Model (Ralph Vince) Signal Extraction (Marc Wildi0...

Frank Harrell is teaching his 3-session short course on regression modeling strategies using R here at Vanderbilt next month. Frank is a professor and chair of the Vanderbilt Biostatistics Department, and the author of several massively popular R libra...

Often times, a scatterplot reveals a pattern that seems not so linear. Polynomial regression can be used to explore a predictor at different levels of curvilinearity. This tutorial will demonstrate how polynomial regression can be used in a hierarchical fashion to best represent a dataset in R.Tutorial FilesBefore we begin, you may want to download the sample...