Following the roundabout tour of F1Stats – A Prequel to Getting Started With Rank Correlations, here’s a walk through of my attempt to replicate the first part of A Tale of Two

Wow, I can’t believe it has been 11 months since my last blog posting! The next series of postings will be related to the retail energy field. Residential power usage is satisfying to model as it can be forecast fairly accurately with the right inputs. Partly as a consequence of deregulation there is now more data more available than...

This morning, Stéphane asked me tricky question about extracting coefficients from a regression with categorical explanatory variates. More precisely, he asked me if it was possible to store the coefficients in a nice table, with information on the variable and the modality (those two information being in two different columns). Here is some code I did to produce the...

I have been working with R for some time now, but once in a while, basic functions catch my eye that I was not aware of… For some project I wanted to transform a correlation matrix into a covariance matrix. Now, since cor2cov does not exist, I thought about “reversing” the cov2cor function (stats:::cov2cor). Inside

Are your for loops too slow in R ? Are loops that should take seconds actually taking hours ? As I found out recently, how you structure your code can make a huge difference in execution times. Fortunately making a few small changes to your code can speed up these loops by several orders of

One of the most common pattern in programming languages is to ability to iterate over a given set (a vector usually) by using 'for' loops. In most modern scripting languages range operations is a build in data structure and trivial to use with 'for' lo...

So, you’ve written some code and you use it routinely. Now you’ve written some code and you’d like to use version control to ensure that development continues in a robust fashion. You do that and you use Github or something so that not only are changes tracked, but the general public receives the benefit of

There is a mechanism that allows variability in the arguments given to R functions. Technically it is ellipsis, but more commonly called “…”, dots, dot-dot-dot or three-dots. Basics The three-dots allows: an arbitrary number and variety of arguments passing arguments on to other functions Arbitrary arguments The two prime cases are the c and list The post The...

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