The R package oro.dicom contains functions for the input/output of medical imaging data that conform to the Digital Imaging and Communications in Medicine (DICOM) standard. This package is part of the Rigorous Analytics bundle. The latest version...

The R package oro.dicom contains functions for the input/output of medical imaging data that conform to the Digital Imaging and Communications in Medicine (DICOM) standard. This package is part of the Rigorous Analytics bundle. The latest version...

The R package oro.dicom contains functions for the input/output of medical imaging data that conform to the Digital Imaging and Communications in Medicine (DICOM) standard. This package is part of the Rigorous Analytics bundle. The latest version...

Update: the competition was just launched. * * * What is the competition about? Drew Conway and John Myles Whyte have collected data from (52) R users about the packages they have installed. The data is now available on github for download and the contest will be run on the kaggle platform. For more details,

Egon writes: Can someone please plot the BioStar users on a Google Map? Sounds like a challenge. Let’s go. 1. Harvesting user IP addresses BioStar user profiles (here’s mine) include a location field. It’s free text and optional, which means that location is missing or inaccurate for many users. However, if you’re logged into BioStar

I’ve modified some routines so that we are always grabbing a roughly equal area regardless of the latitude. Basically, you do this: getLonScaleFactor <- function(lat){ kmAtEq <-111.3195 kmAtLat <- 111.41288*cos(lat*DEGREES.TO.RADIANS)-.09350*cos(3*lat*DEGREES.TO.RADIANS)+0.00012*cos(5*lat*DEGREES.TO.RADIANS) return(kmAtEq/kmAtLat) } # the above function returns a scale factor for km per degree @ a given latitude getExtent <-function(x,halfLength=.5,LonLat) { lonAdjust<-getLonScaleFactor(LonLat)*halfLength yMin <- max(ymin(x),LonLat

Prof. Andrew Gelman, from both the Statistics and Political Science departements at Columbia presented this talk to the New York R Statistical Programming Meetup on October 7, 2010. Description: A challenge in statistics is to construct models that ar...

What makes an R package popular? The number of people that use a given R package is a common point of discussion, but it turns out that it's kind of tricky to get hard and fast data to answer this question. You can look at the "I use this" number on crantastic.org, but that's a self-reported number (many more...

There is a new data mining competition aimed at predicting preferred data mining tools in R via dataists.com. The concept of the competition is to try to determine which R packages are preferred in the R community via their CRAN package librarie...

There is a new data mining competition aimed at predicting preferred data mining tools in R via dataists.com. The concept of the competition is to try to determine which R packages are preferred in the R community via their CRAN package librarie...