Imputing missing values in parallel using {furrr}
{pmice}, an experimental package for missing data imputation in parallel using {mice} and {furrr}
Building formulae
Functional peace of mind
Get basic summary statistics for all the variables in a data frame
Getting {sparklyr}, {h2o}, {rsparkling} to work together and some fun with bash
Importing 30GB of data into R with sparklyr
Introducing brotools
It's lists all the way down
It's lists all the way down, part 2: We need to go deeper
Keep trying that api call with purrr::possibly()
Lesser known dplyr 0.7* tricks
Lesser known dplyr tricks
Lesser known purrr tricks
Make ggplot2 purrr
Mapping a list of functions to a list of datasets with a list of columns as arguments
Predicting job search by training a random forest on an unbalanced dataset
Teaching the tidyverse to beginners
Why I find tidyeval useful
tidyr::spread() and dplyr::rename_at() in action
Easy peasy STATA-like marginal effects with R
Functional programming and unit testing for data munging with R available on Leanpub
How to use jailbreakr
My free book has a cover!
Work on lists of datasets instead of individual datasets by using functional programming
Method of Simulated Moments with R
New website!
Nonlinear Gmm with R - Example with a logistic regression
Simulated Maximum Likelihood with R
Bootstrapping standard errors for difference-in-differences estimation with R
Careful with tryCatch
Data frame columns as arguments to dplyr functions
Export R output to a file
I've started writing a 'book': Functional programming and unit testing for data munging with R
Introduction to programming econometrics with R
Merge a list of datasets together
Object Oriented Programming with R: An example with a Cournot duopoly
R, R with Atlas, R with OpenBLAS and Revolution R Open: which is fastest?
Read a lot of datasets at once with R
Unit testing with R
Update to Introduction to programming econometrics with R
Using R as a Computer Algebra System with Ryacas

This semester, I’ll be teaching an introduction to applied econometrics with R, so I’ve decided to write a very small book called “Introduction to programming Econometrics with R”. This is primarily intended for bachelor students and the focus is not much on econometric theory, but more on how to implement econometric theory into computer code, using the R programming language. It’s very basic and doesn’t cover any advanced topics in econometrics and is intended for people with 0 previous programming knowledge. It is still very rough around the edges, and it’s missing the last chapter about reproducible research, and the references, but I think it’s time to put it out there; someone else than my students may find it useful. The book’s probably full of typos and mistakes, so don’t hesitate to drop me an e-mail if you find something fishy: contact@brodrigues.co

Also there might be some sections at the beginning that only concern my students. Just ignore that.

Get it here: download

You might find the book useful as it is now, but I never had a chance to finish it. I might get back to it once I’ll have more time, and port it to bookdown.