Programming

Bayesian Nonparametrics in R

Bayesian Nonparametrics in R

On July 25th, I’ll be presenting at the Seattle R Meetup about implementing Bayesian nonparametrics in R. If you’re not sure what Bayesian nonparametric methods are, they’re a family of methods that allow you to fit traditional statistical models, such as mixture models or latent factor models, without having to fully specify the number of […]

The Great Julia RNG Refactor

Many readers of this blog will know that I’m a big fan of Bayesian methods, in large part because automated inference tools like JAGS allow modelers to focus on the types of structure they want to extract from data rather than worry about the algorithmic details of how they will fit their models to data. […]

cumplyr: Extending the plyr Package to Handle Cross-Dependencies

Introduction For me, Hadley Wickham‘s reshape and plyr packages are invaluable because they encapsulate omnipresent design patterns in statistical computing: reshape handles switching between the different possible representations of the same underlying data, while plyr automates what Hadley calls the Split-Apply-Combine strategy, in which you split up your data into several subsets, perform some computation […]

Implementing the Exact Binomial Test in Julia

One major benefit of spending my time recently adding statistical functionality to Julia is that I’ve learned a lot about the inner guts of algorithmic null hypothesis significance testing. Implementing Welch’s two-sample t-test last week was a trivial task because of the symmetry of the null hypothesis, but implementing the exact binomial test has proven […]

Floating Point Arithmetic and The Descent into Madness

While I should confess upfront that I’ve always had a weaker command of the details of floating point arithmetic than I feel I ought to have, this sort of thing still blows my mind when I stumble upon it. These moments invariably make me realize that floating point math will simply never satisfy my naive […]

Comparing Julia and R’s Vocabularies

While exploring the Julia manual recently, I realized that it might be helpful to put the basic vocabularies of Julia and R side-by-side for easy comparison. So I took Hadley Wickham’s R Vocabulary section from the book he’s putting together on the devtools wiki, put all of the functions Hadley listed into a CSV file, […]

Using Sparse Matrices in R

Using Sparse Matrices in R

Introduction I’ve recently been working with a couple of large, extremely sparse data sets in R. This has pushed me to spend some time trying to master the CRAN packages that support sparse matrices. This post describes three of them: the Matrix, slam and glmnet packages. The first two packages provide data storage classes for […]

The Psychology of Music and the ‘tuneR’ Package

Introduction This semester I’m TA’ing a course on the Psychology of Music taught by Phil Johnson-Laird. It’s been a great course to teach because (i) so much of the material is new to me and (ii) because the study of the psychology of music brings together so many of the intellectual tools I enjoy, including […]

Visualizing Periodic Data

Yesterday the Princeton machine learning reading group went through a paper by Tukey on “Some graphic and semigraphic displays”. One issue we talked about at length was Tukey’s idiosyncratic approach to visualizing periodic data in a circular format to emphasize the connections between the “start” and the “end” of the data set. Allison Chaney pointed […]

ProjectTemplate News

The news below was recently reported on the ProjectTemplate mailing list. For completeness, I’m also reporting it here. The first piece of ProjectTemplate news is that I won’t be the exclusive maintainer for ProjectTemplate anymore. Allen Goodman, who works at BankSimple, is now my co-maintainer and he has full commit privileges. In the next few […]