In my little world of finance, data almost always is a time series.  Through both quiet iteration and significant revolutions, the volunteers of R have made analyzing and charting time series pleasant.  As a mini-tribute to all those who have... [Read more...]

Generating Tables Using Pander, knitr, and Rmarkdown I use a pretty common workflow (I think) for producing reports on a day to day basis. I write them in rmarkdown using RStudio, knit them into .html and .md documents using knitr, then convert the resulting .md file to a .docx file ... [Read more...]

highlight 0.4.2 is on CRAN. This fixes a few bugs reported by users. The main improvement is that we can now use highlight as a vignette engine, using the functionality introduced in R 3.0.0. In the Rcpp universe, we use … Continue reading → [Read more...]

I’ll be presenting at the Dallas R Users Group next Saturday at 10:00AM at the University of Dallas on how to reproduce your R code. We’ll review how to use R scripts, how to embed R code in reproducible documents, and then introduce how to create your own ... [Read more...]

Last week, a colleague draw my attention on this new log files from the Rstudio cloud CRAN mirror, through a post from Tal Galili. This CRAN mirror is a little different, as it uses Amazon CloudFront to deliver the downloads … Continue reading → [Read more...]

In the last few years there has been a increasing tendency to ignore the value of a disciplined quantitative approach to the portfolio allocation process in favor of simple and static weighting schemes such as equal weighting or some type of adjusted volatility weighting. The former simply ignores the underlying ... [Read more...]

I recently was faced with the desire to port some tree models developed in R to SAS so I could score a large database. To me this makes sense as SAS is better with large files (or at least so as not to offend anyone, I am better with large ... [Read more...]

Yesterday, I was creating a knitr document based on a script, and was looking for a way to include content from an R help file. The script, which was a teaching document, had a help() command for when the author wanted to refer readers to R documentation. I wanted that ... [Read more...]

As we believe you may know, we are having a webinar tomorrow (June 19th, 2013) on Predictive Analytics. During this webinar, you are going to be introduced to R, learn how to build a predictive model and also how to carry insightful analysis through visualization. As learning a new language can ... [Read more...]

After months of work (although to be fair, we haven't worked 100% full time on this), Andrea and I are nearly ready to publish the next release of BCEA. Andrea has done a brilliant job and is responsible for most of the good new features (NB: see ... [Read more...]

One of the greatest challenges while working with big datasets concerns the need to move information out of storage for analysis. To this end, the recent announcement of PivotalR 0.1 extends Pivotal HD's capabilities, allowing users of the statistical programming language R to perform in-database analytics without leaving the command line. [Read more...]

library(rgdal)library(raster)alt gadm gadm_sub plot(alt)plot(gadm_sub, add=T)asp slo __ extract(slo, gadm_sub, fun = mean, na.rm = T, small = T, df = T) ID slope1 1 9.9590532 2 1.0474433 3 7.4561654 4 1.6737865 5 11.946553__ extract(asp, gadm_sub, fun = mean, na.rm = T, small = T, df = T) ID aspect1 1 170.80652 2 184.01303 3 190.71554 4 136.89535 5 205.2115 [Read more...]

Following up on a suggestion from my previous post, here are the statistics for medal count versus age. Every point on the plot is the number (see colour legend on right) of athletes who have achieved a given number of medals by a particular age. There is clear evidence of ... [Read more...]

I suppose most companies use the Microsoft Office suite of programs, and my office is no exception. It easy to import data from an API or a database into R, but importing data from an Excel workbook is a different story. There are a few R packages for reading Excel ... [Read more...]

Postdoctoral position in statistical modeling of social networks A full-time postdoctoral position is available beginning Fall 2014 in the research group of Tian Zheng and Andrew Gelman working on statistical analysis and modeling of social network data, in close cooperation with our experimental collaborators. Four key papers of this project so ... [Read more...]

Here's a little r-script to convenientely download high quality digital elevation data, i.e. for the Alps, from HERE:require(XML)dir.create("D:/GIS_DataBase/DEM/")setwd("D:/GIS_DataBase/DEM/")doc urls names for (i in 1:length(urls)) download.file(urls[i], names[i]) # unzip all files in ... [Read more...]

As those of you who read my last post know, I’m at the NIMBioS-CAMBAM workshop on linking mathematical models to biological data here at UT Knoxville. Day 1 (today) was on parameter estimation and model identifiability. Specifically, we (quickly) covered … Continue reading → [Read more...]

The Google Charts Tools provide two kinds of heat map charts for geographical data, the Flash based Geomap and the HTML5/SVG based Geochart. I prefer the Geochart as it doesn't require Flash, but so far there have been two shortcomings with it: I couldn't add additional tooltip information and ... [Read more...]

Graphs can be an important feature of analysis. A graph that has been well designed and put together can make summary statistics much more readable and increase the interpretability. It also makes reports and articles looks more professional. There are many software packages that are available to design great graphs ... [Read more...]

Sharon Machlis is not only the online managing editor at Computerworld, she's also a budding data scientist who recently started learning the R language. To the benefit of all other new R users, she's shared her learnings in an excellent 6-part beginners guide to R, published by Computerworld. It's jam-packed ... [Read more...]