R-bloggers

As you’re learning R, it can be hard to come up with data sets that you can practice with. Though many of us have our own data, those might not always be in the best format to do what we want. Our own data are often messy and require ...

How many times has your code unexpectedly stopped working? Even better, how many times did the code work on your machine, but your coworkers couldn’t run it? Both questions share the same underlying problem – R environment. That’s where R renv comes in – a dependency management package that will ...

Every data science project needs a data validation step. It’s a crucial part, especially when feeding data into machine learning models. You don’t want errors or unexpected behaviors in a production environment. Data validation is a way you can check the data before it touches the model and ...

Introduction Cumulative mean is a statistical measure that calculates the mean of a set of numbers up to a certain point in time or after a certain number of observations. It is also known as a running average or moving average. Cumulative mean ...

My posts are usually R only. But in this post, I want to talk about a suite of tools developed by my colleagues and me that goes beyond R only. This suite of tools helps to gather results from different search engines and includes a browser extension to scrape the ...

Are you tired of creating lag variables one by one? Are you ready to level up your time series analysis game? Forget everything you know about creating lag variables. There’s a better way, and it’s been right in front of you all along. This is a good one. ...

When interviewing impressive applicants from a stunning variety of places and background for fellows in our Data Science for Social Good program (in Warwick and Kaiserslautern) this summer, we came through the common conundrum of comparing ranks while each of us only meeting a subset of the candidates. Over a ...

Introduction: What is Rank Dependent Utility? Rank dependent utility theory made its debut in John Quiggin’s 1982 paper “A Theory of Anticipated Utility” with the mission, similar to other papers at the time, to come up with a model which addressed the Allais Paradox which was a major problem for ...

Hey, JAGS users and would-be users, be warned that registration is now open for the annual JAGS workshop on probabilistic modelling for cognitive science. The tenth instalment of this workshop takes place July 10–14, 2023 in Amsterdam and online. This workshop is meant for researchers who want to learn how to apply ...

The first thing I thought when I tried all the cool tools of the Year of the AI Revolution (aka 2022) was: OMG this is amazing, it’s the AI future that I never thought I would see. The second thing I thought was: OMG this is going to be used ...

Prospect theory made its debut back in 1979 and was one of the first major attempts to address empirical deviations from expected utility theory. One of the key ingredients in operationalizing prospect theory involve conversion of probabilities to “weighted probabilities”. It should be noted that while there are more advanced libraries ...

Introduction Recently, I released a R package called starBliss that aimed to replicate the output of a e-commerce site called MapsForMoments – a site which lets users order custom prints of the night sky on the date of their choosing (usually a special occasion such as a birthday, first date, wedding ...

What’s the one thing that help you add value to your company’s raw geospatial data? GEOCODING. Geocoding is the process of converting raw physical addresses to latitude and longitude geospatial points that can be viewed on a map and used for geospatia...