May 2013

Rによるモンテカルロ法入門

May 13, 2013 | xi'an

Here is the cover of the Japanese translation of our Introducing Monte Carlo methods with R book.  A few year after the French translation. It actually appeared last year in August but I was not informed of this till a few weeks ago. The publisher is Maruzen, with an associated ... [Read more...]

Integration take two – Shiny application

May 13, 2013 | beckmw

My last post discussed a technique for integrating functions in R using a Monte Carlo or randomization approach. The mc.int function (available here) estimated the area underneath a curve by multiplying the proportion of random points below the curve by the total area covered by points within the interval: ... [Read more...]

In case you missed it: April 2013 Roundup

May 13, 2013 | David Smith

In case you missed them, here are some articles from April of particular interest to R users: A critique of a SAS whitepaper comparing the performance of SAS, R and Mahout. A video presentation from statistician Tess Nesbitt at UpStream, who uses GAM survival models in R for marketing attribution ... [Read more...]

Shiny App for CRAN packages

May 13, 2013 | pssguy

Over the past few days, I have been introduced to a few new-to-me R packages, via some comments from the Shiny guys and the R-bloggers site. This seems a rather haphazard way of acquiring knowledge and I cannot be alone in thinking that this is not the most productive way ... [Read more...]

Stack Exchange: Why I dropped out

May 13, 2013 | Karl Broman

Stack Exchange is a series of question-and-answer sites, including Stack Overflow for programming and Cross Validated for statistics. I was introduced to these sites at a short talk by Barry Rowlingson at the 2011 UseR! meeting, “Why R-help must die!“ These sites have a lot of advantages over R-help: The format ... [Read more...]

Global Indicator Analyses with R

May 13, 2013 | bryan

I was recently asked by a client to create a large number of “proof of concept” visualizations that illustrated the power of R for compiling and analyzing disparate datasets. The client was specifically interested in automated analyses of global data. A little research led me to the WDI package. The ... [Read more...]

Living it up with computational errors

May 13, 2013 | Patrick Burns

How to have a better chance of a good outcome. Making mistakes There’s been a lot of talk recently about data analysis problems with spreadsheets.  If you’ve not stuck your head out of your cave lately, then you can catch some of the discussion by doing an internet ... [Read more...]

Combining dataframes when the columns don’t match

May 13, 2013 | Amy Whitehead

Most of my work recently has involved downloading large datasets of species occurrences from online databases and attempting to smoodge1 them together to create distribution maps for parts of Australia. Online databases typically have a ridiculous number of columns with … Continue reading → [Read more...]

The Guerilla Guide to R

May 12, 2013 | Nikhil Gopal

Update: Okay. I've uploaded a new template and things seem to be fine now. Update: I am aware the table of contents is not being displayed in bullet form as I intended. The web template I'm using seems to be buggy. It also seems to think this page is in ... [Read more...]

awalé

May 12, 2013 | xi'an

Following Le Monde puzzle #810, I tried to code an R program (not reproduced here) to optimise an awalé game but the recursion was too rich for R: even with a very small number of holes and seeds in the awalé… Searching on the internet, it seems the computer simulation of ... [Read more...]

Using C libraries in R with rdyncall

May 12, 2013 | f3lix

One reason I like using R for data analysis is that R has a great collection of packages that let you easily apply state-of-the-art methods to your problems. But once in a while you find a library that you would like to use that does not have a R wrapper, ... [Read more...]

A new package : Quandl

May 12, 2013 | G-Tch

Quandl is a new database management tool which seeks to become the place to find datasets. That is, each unique indicator is considered an independent data set. This helps them to seem to have a ginormous quantity of data sets. Source : Blog Econo...
[Read more...]

Reshaping data

May 12, 2013 | Wingfeet

Preparing and reshaping data is the ever continuing task of a data analyst. Luckily we have many tools for it. The default tool in R would be reshape(), although this is so user friendly that a reshape package has been added too. I try to use reshape()... [Read more...]

Playing cards, with R

May 11, 2013 | arthur charpentier

In my courses on R, I usually show how to insert a picture as a background for a graph. But it is also to see the picture as an object, and to insert it in a graph everywhere we like to see it, as explained on the awesome blog http://... [Read more...]

Animations Understood

May 11, 2013 | tylerrinker

When I first saw a graphic made from Yihui’s animation package (Xie, 2013) I was amazed at the magic and thought “I could never do that”. Passage of time… One night I found myself bored and as usual avoiding work. … Continue reading → [Read more...]

Reproducibility and randomness

May 11, 2013 | arthur charpentier

With Stéphane Tufféry, we were working this week on a chapter of a book, entitled Statistical Learning in Actuarial Science. The chapter should be based on R functions, and we wanted to reproduce some outputs he previously obtained with SAS. The good thing is that even complex functions (... [Read more...]
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