Data analysis deals with different kinds of data. For instance we can have supermarket sales with - a transactional table, with customer ID, item ID, date of purchase - an item table, with the item ID and its price - … Continue reading → [Read more...]

Introduction A wise person told me that it will be a full moon on the upcoming Valentine’s Day, but that it will be a long time until another one. I decided to check this with astronomical calculation. Procedure The Oce package has a function called moonAngle() that returns, among ... [Read more...]

The registration for the second conference on R in Insurance on Monday 14 July 2014 at Cass Business School in London has opened. This one-day conference will focus again on applications in insurance and actuarial science that use R, the lingua franca for statistical computation. Topics covered may include actuarial statistics, capital ... [Read more...]

It is my great pleasure to share with you a breakthrough in statistical computing. There are many statistical tests: the t-test, the chi-squared test, the ANOVA, etc. I here present a new test, a test that answers the question researchers are most anxious to figure out, a test of significance, ... [Read more...]

In my first post, I described the general logic of Bayes factors. I will continue discussing the general logic of Bayes factor, while introducing some of the basic functionality of the BayesFactor package.Recap: What is a Bayes factor?The Bayes factor is the relative evidence provided by the data ... [Read more...]

Last year, I did mention in a post that unit-root tests are dangerous, because they might lead us to strange models. For instance, in a post, I did obtain that the temperature observed in January 2013, in Montréal, might be considered as a random walk process (or at leat an ... [Read more...]

This week, in the MAT8181 Time Series course, we’ve discussed unit root tests. According to Wold’s theorem, if is  (weakly) stationnary then where is the innovation process, and where  is some deterministic series (just to get a result as general as possible). Observe that as discussed in a ... [Read more...]

I’m posting this mostly to show how to: use the Google spreadsheet data-munging “hack” from the previous post in a Shiny context include it seamlessly into a web page, and run it locally without a great deal of wrangling The code for the app is in this gist. It ... [Read more...]

I have been using third party programs for a long time until i came across the documentation for the R-package digitize. unfortunately, this package is not available for R 3.0.2 so i had to tweek things around. I am glad to share my solution. I started by taking a look at ... [Read more...]

by Oliver Vagner, Cloud Solutions Lead Architect at Revolution Analytics Today, I am pleased to announce our new offering in the Amazon Web Services Big Data Marketplace – Revolution R Enterprise 7 for AWS. Of course, if you follow this blog, then you are quite familiar with Revolution R Enterprise (RRE) and ... [Read more...]

A new release 0.2.11 of RInside is now on CRAN. RInside provides a set of convenience classes which facilitate embedding of R inside of C++ applications and programs, using the classes and functions provided by the Rcpp R and C++ integration package... [Read more...]

A new version of my hts package for R is now on CRAN. It was completely re-written from scratch. Not a single line of code survived. There are some minor syntax changes, but the biggest change is speed and scope. This version is many times faster than the previous version ... [Read more...]

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In a recent blog post we discussed caching calls to the web offline, on your own computer. Just like you can cache data on your own computer, a data provider can do the same thing. Most of the data providers we work with do not provide caching. However, at least ... [Read more...]

Two recent salary surveys have shown that R language skills attract median salaries in excess of $110,000 in the United States. In the 2014 Dice Tech Salary Survey of over 17,000 technology professionals, the highest-paid IT skill was R programming. While big-data skills in general featured strongly in the top tier, having R ... [Read more...]

In quantitative finance both R and Excel are the basis tools for any type of analysis. Whenever one has to use Excel in conjunction with R, there are many ways to approach the problem and many solutions. It depends on what you really want to do and the size of ... [Read more...]

The “medals” R post by TRInker and re-blogged by Revolutions were both spiffy and a live example why there’s no point in not publishing raw data. You don’t need to have R (or any other language) do the scraping, though. The “IMPORTHTML” function (yes, function names seem to ... [Read more...]

At the moment, the world is obsessed with “Big Data” yet it sometimes seems that people who use this phrase don’t have a good grasp of its meaning.  Like most good buzz-words, “Big Data” sparks the idea of something grand and complicated, while sounding ordinary enough that listeners feel ... [Read more...]

This video was created by Dr. Roger Peng, professor at the Johns Hopkins Bloomberg School of Public Health and author at Simply Statistics. Dr. Peng is not affiliated with Stats Make Me Cry in any way and written consent was ob... [Read more...]

How to get parameter-specific p-values is one of the most commonly asked questions about multilevel regression. The key issue is that the degrees of freedom are not trivial to compute for multilevel regression. Various detailed discussions can be found on the R-wiki and R-help mailing list post by Doug Bates. ... [Read more...]