Yesterday, my friend Fleur did show me some interesting features of the leaflet package, in R. library(leaflet) In order to illustrate, consider locations of (fixed) radars, in several European countries. To get the data, use download.file("http://carte-gps-gratuite.fr/radars/zones-de-danger-destinator.zip","radar.zip") unzip("radar.zip")   ext_...

Tuesday, at the end of my 5-hour crash course on machine learning for actuaries, Pierre asked me an interesting question about computational time of different techniques. I’ve been presenting the philosophy of various algorithm, but I forgot to mention computational time. I wanted to try several classification algorithms on ...

This week, I mentioned a series of maps, on Twitter, some minimalist maps http://t.co/YCNPf3AR9n (poke @visionscarto) pic.twitter.com/Ip9Tylsbkv — Arthur Charpentier (@freakonometrics) 2 Septembre 2015 Friday evening, just before leaving the office to pick-up the kids after their first week back in class, Matthew Champion (...

Mid november, a nice workshop on big data and environment will be organized, in Argentina, We will talk a lot about climate models, and I wanted to play a little bit with those data, stored on http://dods.ipsl.jussieu.fr/mc2ipsl/. Since Ewen (aka @3wen) has been working ...

This afternoon, we’ve seen in the training on data science that it was possible to use AIC criteria for model selection. __ library(splines) __ AIC(glm(dist ~ speed, data=train_cars, family=poisson(link="log"))) [1] 438.6314 __ AIC(glm(dist ~ speed, data=train_cars, family=poisson(link="identity"))) [1] 436.3997 __ AIC(glm(dist ~ bs(...

A few years ago, I did publish a post to visualize and empirical claims frequency in a portfolio. I wanted to update the code. Here is a code to get a dataset, sinistre

In order to illustrate the problem of chosing a classification model consider some simulated data, __ n = 500 __ set.seed(1) __ X = rnorm(n) __ ma = 10-(X+1.5)^2*2 __ mb = -10+(X-1.5)^2*2 __ M = cbind(ma,mb) __ set.seed(1) __ Z = sample(1:2,size=n,replace=TRUE) __ Y = ma*(Z==1)+mb*(Z==2)+rnorm(n)*5 __ df = data.frame(Z=...

Classification trees are nice. They provide an interesting alternative to a logistic regression.  I started to include them in my courses maybe 7 or 8 years ago. The question is nice (how to get an optimal partition), the algorithmic procedure is nice (the trick of splitting according to one variable, and only ...

Yesterday evening, I discovered some interesting slides on False-Positives, p-Hacking, Statistical Power, and Evidential Value, via @UCBITSS ‘s post on Twitter. More precisely, there was this slide on how cheating (because that’s basically what it is) to get a ‘good’ model (by targeting the p-value) As mentioned by @david_...

Disclamer: This is a joint post with Avner Bar-Hen, a.k.a. @a_bh, Benjamin Guedj, a.k.a. @bguedj and Nathalie Villa, a.k.a. @Natty_V2 Organised annually since 1970 by the French Society of Statistics (SFdS), the Journées de Statistique (JdS) are the most important scientific event ...

This Tuesday, I will be in Leuven (in Belgium) at the ACP meeting to give  a talk on Data Science: from Small to Big Data. The talk will take place in the Faculty Club from 6 till 8 pm. Slides could be found online (with animated pictures). As usual, comments are welcome.