Articles by Higher Order Functions

Bayes’ theorem in three panels

March 4, 2020 | 0 Comments

In my last post, I walked through an intuition-building visualization I created to describe mixed-effects models for a nonspecialist audience. For that presentation, I also created an analogous visualization to introduce Bayes’ Theorem, so here I will walk through that figure.. As in the earlier post, let’s start by ...
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Another mixed effects model visualization

November 25, 2019 | 0 Comments

Last week, I presented an analysis on the longitudinal development of intelligibility in children with cerebral palsy—that is, how well do strangers understand these children’s speech from 2 to 8 years old. My analysis used a Bayesian nonlinear mixed effects Beta regression model. If some models are livestock and some ...
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ICC Bot comes online

September 17, 2019 | 0 Comments

I am happy to announce the release of ICC Bot, an app for computing interrater reliability scores using the intraclass correlation coefficient (ICC). A screenshot of ICC Bot, an interactive app for computing intraclass correlation coefficients. The ICC statistic appears in repeated measures or multilevel modeling literature as a way ...
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Anatomy of a logistic growth curve

February 15, 2019 | 0 Comments

In this post, I walk through the code I used to make a nice diagram illustrating the parameters in a logistic growth curve. I made this figure for a conference submission. I had a tight word limit (600 words) and a complicated statistical method (Bayesian nonlinear mixed effects beta regression), so ...
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sample_n_of(): a useful helper function

May 23, 2018 | 0 Comments

Here’s the problem: I have some data with nested time series. Lots of them. It’s like there’s many, many little datasets inside my data. There are too many groups to plot all of the time series at once, so I just want to preview a handful of ...
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10 PRINT mazes with ggplot2

May 8, 2018 | 0 Comments

There is a celebrated Commodore 64 program that randomly prints outs / and \ characters and fills the screen with neat-looking maze designs. It is just one line of code, but there is a whole book written about it. 10 PRINT CHR$(205.5+RND(1)); : GOTO 10 Screenshots of the 10 PRINT program in action. Images taken from ...
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Ridgelines in bayesplot 1.5.0

April 2, 2018 | 0 Comments

At the end of March, Jonah Gabry and I released bayesplot 1.5.0. The major additions to the package were visualizations using ridgelines and a new plot for PIT diagnostics from LOO validation. I don’t know what that LOO PIT thing is yet, so I’ll ta...
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Using nonstandard evaluation to simulate a register machine

January 5, 2018 | 0 Comments

I recently completed all 25 days of Advent of Code 2017, an annual series of recreational programming puzzles. Each day describes a programming puzzle and illustrates a handful of simple examples of the problem. The puzzle then requires the participant to solve a much, much larger form of the problem. For five ... [Read more...]

Secret Santa is a graph traversal problem

November 28, 2017 | 0 Comments

Last week at Thanksgiving, my family drew names from a hat for our annual game of Secret Santa. Actually, it wasn’t a hat but you know what I mean. (Now that I think about it, I don’t think I’ve ever seen names drawn from a literal hat ... [Read more...]

Simplifying ggplot2 code by doing nothing

October 10, 2017 | 0 Comments

Recently, I joined the development team for bayesplot, an R package by the Stan team for plotting Bayesian models. Because visualizing Bayesian models in ggplot2 is a recurring topic here, it was a natural fit. So from time to time, I’ll post about some programming techniques and new features ...
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set_na_where(): a nonstandard evaluation use case

August 14, 2017 | 0 Comments

In this post, I describe a recent case where I used rlang’s tidy evaluation system to do some data-cleaning. This example is not particularly involved, but it demonstrates is a basic but powerful idea: That we can capture the expressions that a user...
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A tour of the tibble package

July 9, 2017 | 0 Comments

Dataframes are used in R to hold tabular data. Think of the prototypical spreadsheet or database table: a grid of data arranged into rows and columns. That’s a dataframe. The tibble R package provides a fresh take on dataframes to fix some longstan... [Read more...]

Plotting partial pooling in mixed-effects models

June 21, 2017 | 0 Comments

In this post, I demonstrate a few techniques for plotting information from a relatively simple mixed-effects model fit in R. These plots can help us develop intuitions about what these models are doing and what “partial pooling” means. The sleeps...
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I don’t know Fisher’s exact test, but I know Stan

May 15, 2017 | 0 Comments

A few days ago, I watched a terrific lecture by Bob Carpenter on Bayesian models. He started with a Bayesian approach to Fisher’s exact test. I had never heard of this classical procedure, so I was curious to play with the example. In this post, I use the same ...
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Simulating Unown encounter rates in Pokémon Go

March 21, 2017 | 0 Comments

Pokémon Go is an augmented reality game where people with smartphones walk around and catch Pokémon. As in the classic games, players are Pokémon “trainers” who have to travel around and collect creatures. Some types are rarer than others, som...
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Repeatedly applying a function

January 11, 2017 | 0 Comments

A colleague of mine sent me the following R question: I have a function that takes a list and does some stuff to it and then returns it. I then take that output and run it through the same function again. But I obviously don’t want to repeatedly ...
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RStanARM basics: visualizing uncertainty in linear regression

November 18, 2016 | 0 Comments

As part of my tutorial talk on RStanARM, I presented some examples of how to visualize the uncertainty in Bayesian linear regression models. This post is an expanded demonstration of the approaches I presented in that tutorial. Data: Does brain mass predict how much mammals sleep in a day? Let’...
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Recent adventures with lazyeval

August 14, 2016 | 0 Comments

The lazyeval package is a tool-set for performing nonstandard evaluation in R. Nonstandard evaluation refers to any situation where something special happens with how user input or code is evaluated. For example, the library function doesn’t evalua...
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