Blog Archives

R Courses at Newcastle

April 22, 2016
By
R Courses at Newcastle

Over the next two months I’m running a number of R courses at Newcastle University. May 2016 May 10th, 11th: Predictive Analytics May 16th – 20th: Bioconductor May 23rd, 24th: Advanced programming June 2016 June 8th: R for Big Data June 9th: Interactive graphics with Shiny Since these courses are on  advanced topics, numbers are limited

Read more »

RStudio addins manager

March 31, 2016
By
RStudio addins manager

RStudio addins let you execute a bit of R code or a Shiny app through the RStudio IDE, either via the Addins dropdown menu or with a keyboard shortcut. This package is an RStudio addin for managing other addins. To run these addins, you need the latest version of RStudio. Installation The package can be

Read more »

RANDU: The case of the bad RNG

February 16, 2016
By
RANDU: The case of the bad RNG

The German Federal Office for Information Security (BSI) has established criteria for quality random number generator (rng): A sequence of random numbers has a high probability of containing no identical consecutive elements. A sequence of numbers which is indistinguishable from true random’ numbers (tested using statistical tests. It should be impossible to calculate, or guess,

Read more »

Shiny benchmarks

February 15, 2016
By
Shiny benchmarks

A couple of months ago, the first version of benchmarkme was released. Around 140 machines have now been benchmarked. From the fastest (an Apple i7) which ran the tests in around 10 seconds, to the slowest (an Atom(TM) CPU N450 @ 1.66GHz) which took 420 seconds! Other interesting statistics: Around 6% of people ran BLAS

Read more »

Crowd sourced benchmarks

December 1, 2015
By
Crowd sourced benchmarks

When discussing how to speed up slow R code, my first question is what is your computer spec? It always surprises me when complex biological experiments, costing a significant amount of money, are analysed using a six year old laptop. A new desktop machine costs around £1000 and that money would be saved within a

Read more »

useR 2015: Computational

July 1, 2015
By
useR 2015: Computational

These are my initial notes from useR 2015. I will/may revise when I have time. Computational Performance; Chair: Dirk Eddelbuettel Running R+Hadoop using Docker Containers (E. James Harner) Introduction Big data architectures: HDFS/Hadoop: software framework for distributed storage and distributed processing Tachyon/Spark: uses in-memory Rc2 server (R cloud computing) Has an editor & output panel.

Read more »

useR 2015: Computational

July 1, 2015
By
useR 2015: Computational

These are my initial notes from useR 2015. I will/may revise when I have time. Computational Performance; Chair: Dirk Eddelbuettel Running R+Hadoop using Docker Containers (E. James Harner) Introduction Big data architectures: HDFS/Hadoop: software framework for distributed storage and distributed processing Tachyon/Spark: uses in-memory Rc2 server (R cloud computing) Has an editor & output panel.

Read more »

useR 2015: Networks

July 1, 2015
By
useR 2015: Networks

These are my initial notes from useR 2015. Will revise when I have time. fbRads: Analyzing and managing Facebook ads from R (Gergely Daroczi) Modern advertising Google/Amazon/Facebook use our information Ad platforms: Google: RAdwords, facebook likes: fbRads. You can use the facebook API to get information from facebook. Get hashes of email address, not the

Read more »

useR 2015: Networks

July 1, 2015
By
useR 2015: Networks

These are my initial notes from useR 2015. Will revise when I have time. fbRads: Analyzing and managing Facebook ads from R (Gergely Daroczi) Modern advertising Google/Amazon/Facebook use our information Ad platforms: Google: RAdwords, facebook likes: fbRads. You can use the facebook API to get information from facebook. Get hashes of email address, not the

Read more »

useR 2015: Romain Francois: My R adventures

July 1, 2015
By
useR 2015: Romain Francois: My R adventures

Using R since 2002 and has been working on Rcpp, Rcpp11, Rcpp14 and dplyr internals. Worked on a number of big projects. 2005 he set up the R Graph Gallery 2009 worked on rJava 2010 Rcpp 2013 dplyr Key themes are Performance and usabililty rJava 0.7-* Creating objects was messy d <-jnew("java/lang/Double", 42 .jcal(d, "D",

Read more »

Sponsors

Never miss an update!
Subscribe to R-bloggers to receive
e-mails with the latest R posts.
(You will not see this message again.)

Click here to close (This popup will not appear again)