Author: R-Bloggers

Feed: R-bloggers. Author: Stéphane Laurent. [This article was first published on Saturn Elephant, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here) Want to share your content on R-bloggers? click here if you have a blog, or here if you don't. My new package ‘gfiExtremes’ is on CRAN now. So it is time to present it. This package allows to get confidence intervals about the quantiles of any reasonable distribution (although the inference is based on a parametric model). The statistical inference is fiducial. To give an illustration, I’m taking a sample of ... Read More

Feed: R-bloggers. Author: An Accounting and Data Science Nerd's Corner. [This article was first published on An Accounting and Data Science Nerd's Corner, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here) Want to share your content on R-bloggers? click here if you have a blog, or here if you don't. As a package maintainer you might be observing an increasing number of questions raised by people that have recently migrated to R 4.0.0 and are now trying to get your package to work. Yet, rhub::check_with_rrelease() currently still uses R 3.6.3 as test ... Read More

Feed: R-bloggers. Author: Bluecology blog. [This article was first published on Bluecology blog, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here) Want to share your content on R-bloggers? click here if you have a blog, or here if you don't. Time sinks for data wrangling Estimating the time it will take to complete a project is an important part of being a successful PhD student, researcher or consultant. A major time sink on many analytical projects is data wrangling. Often the wrangling can take longer than the analysis. Here’s some good questions ... Read More

Feed: R-bloggers. Author: Paul van der Laken. [This article was first published on r – paulvanderlaken.com, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here) Want to share your content on R-bloggers? click here if you have a blog, or here if you don't. I really like generative art, or so-called algorithmic art. Basically, it means you take a pattern or a complex system of rules, and apply it to create something new following those patterns/rules. When I finished my PhD, I got a beautiful poster of where the k-nearest neighbors algorithms was ... Read More

Feed: R-bloggers. Author: . As I was preparing some graphics for a presentation recently, I started digging into some of the different color palette options. My motivation was entirely about creating graphics that weren’t too visually overwhelming, which I found the default “rainbow” palette to be. But as the creators of the viridis R package point out, we also need to think about how people with colorblindness might struggle with understanding graphics. If you create figures in R, I highly recommend checking it out at the link above! To leave a comment for the author, please follow the link and ... Read More

Feed: R-bloggers. Author: . As I conduct some analysis for a content validation study, I wanted to quickly blog about a fun plot I discovered today: ggpairs, which displays scatterplots and correlations in a grid for a set of variables. To demonstrate, I’ll return to my Facebook dataset, which I used for some of last year’s R analysis demonstrations. You can find the dataset, a minicodebook, and code on importing into R here. Then use the code from this post to compute the following variables: RRS, CESD, Extraversion, Agree, Consc, EmoSt, Openness. These correspond to measures of rumination, depression, and ... Read More

Feed: R-bloggers. Author: . Stacked Bar Chart for Rank Data At work on Friday, I was trying to figure out the best way to display some rank data. What I had were rankings from 1-5 for 10 factors considered most important in a job (such as Salary, Insurance Benefits, and the Opportunity to Learn), meaning each respondent chose and ranked the top 5 from those 10, and the remaining 5 were unranked by that respondent. Without even thinking about the missing data issue, I computed a mean rank and called it a day. (Yes, I know that ranks are ordinal ... Read More

Feed: R-bloggers. Author: . In my last Statistics Sunday post, I briefly mentioned the concept of regular expressions, also known as regex (though note that in some contexts, these refer to different things – see here). A regular expression is a text string, which you ask your program to match. You can use this to look for files with a particular name or extension, or search a corpus of text for a specific word or word(s) that match a certain pattern. This concept is used in many programming languages, and R is no exception. In order to use a regular ... Read More

Feed: R-bloggers. Author: . First Statistics Sunday in far too long! It’s going to be a short one, but it describes a great trick I learned recently while completing a time study for our exams at work. To give a bit of background, this time study involves analzying time examinees spent on their exam and whether they were able to complete all items. We’ve done time studies in the past to select time allowed for each exam, but we revisit on a cycle to make certain the time allowed is still ample. All of our exams are computer-administered, and we ... Read More

Feed: R-bloggers. Author: . Two statistical indices crossed my inbox in the last week, both of which use fast food restaurants to measure a concept indirectly. First up, in the wake of recent hurricanes, is the Waffle House Index. As The Economist explains: Waffle House, a breakfast chain from the American South, is better known for reliability than quality. All its restaurants stay open every hour of every day. After extreme weather, like floods, tornados and hurricanes, Waffle Houses are quick to reopen, even if they can only serve a limited menu. That makes them a remarkably reliable if informal ... Read More