tl;dr: To avoid triple quotes and R CMD CHECK --as-cran errors due to documentation examples for internal functions, enclose the example code in \dontrun{}. I recently encountered an issue when submitting an R package to CRAN that I couldn’t find … Continue reading →

(Note: The code in this post is available here as a single R script.) Let’s say A and B play 7 games and A wins 4 of them. What would be a reasonable estimate for A’s win probability (over B)? … Continue reading →

Background With the NBA playoffs going on, I’ve been thinking about the following question: A and B are about to play a game. We know that among all players, A has rank/seed and B has rank/seed . (A higher ranking/seeding … Continue reading →

TLDR: I’ve written an R package, cvwrapr, that helps users to cross-validate hyperparameters. The code base is largely extracted from the glmnet package. The R package is available for download from Github, and contains two vignettes which demonstrate how to … Continue reading →

The Tukey loss function The Tukey loss function, also known as Tukey’s biweight function, is a loss function that is used in robust statistics. Tukey’s loss is similar to Huber loss in that it demonstrates quadratic behavior near the origin. … Continue reading →

I recently heard that Manchester City were so far ahead in the English Premier League (EPL) that the race for first was basically over, even though they were still about 6-7 more games to go (out of a total of … Continue reading →

Happy Pi Day! I don’t encounter very much in my area of statistics, so this post might seem a little forced… In this post, I’m going to show one way to estimate . The starting point is the integral identity … Continue reading →

A sunflower plot is a type of scatterplot which tries to reduce overplotting. When there are multiple points that have the same (x, y) values, sunflower plots plot just one point there, but has little edges (or “petals”) coming out … Continue reading →

(This is a PSA post, where I share a package that I think that might be of interest to the community but I haven’t looked too deeply into myself.) Today I learnt of the covidcast R package, which provides access … Continue reading →

The Mendoza Line is a term from baseball. Named after Mario Mendoza, it refers to the threshold of incompetent hitting. It is frequently taken to be a batting average of .200, although all the sources I looked at made sure … Continue reading →

Toss Up! is a very simple dice game that I’ve always wanted to simulate but never got around to doing so (until now!). This post outlines how to simulate a Toss Up! game in R, as well as how to … Continue reading →

My daughter received the board game First Orchard as a Christmas present and she’s hooked on it so far. In playing the game with her, a few probability/statistics questions came to mind. This post outlines how I answered some of … Continue reading →

I recently learnt how to build basic R Shiny apps. To practice using Shiny, I created a simple app that you can use to perform simple exploratory data analysis. You can use the app here to play around with the … Continue reading →

Background In the linear regression context, it is common to use the F-test to test whether a proposed regression model fits the data well. Say we have predictors, and we are comparing the model fit for Linear regression where are … Continue reading →

If you’ve ever visited this blog at wordpress.com, you might have noticed a header image that looks like this: Ever wonder how it was generated? The image depicts 100 simulations of an asymmetric random walk. In this post, I’ll go … Continue reading →