With a little guidance from the indefatigable Hadley Wickham, I figured out today how to implement the setter methods that were missing from my example user class. To review, let’s rebuild the getter methods for my user object: 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17
Blog Archives
The Most Basic Elements of Object-Oriented Programming in R
Until recently, I’ve never had any reason to learn how to define my own classes in R. Having learned this week, I was surprised to find out how easy it is to start implementing classes in R. If you know nothing about creating classes and class methods in R, here’s a very quick overview of
A Lot of Deaths are Partly Self-Induced
I’m a little surprised by Andrew Gelman’s post today, doubting the wisdom of a passage from Gary Becker’s work that reads: According to the economic approach, therefore, most (if not all!) deaths are to some extent “suicides” in the sense that they could have been postponed if more resources had been invested in prolonging life.
Times Series Methods versus Recurrence Relations
This term, I’ve been sitting in on Rene Carmona’s course on Modern Regression and Time Series Analysis. Much of the material on regression covered in the course was familiar to me already, but I’ve never felt that I had a real command of times series analysis methods. When Carmona defined the AR(p) model in class
R Function Usage Frequencies, Addendum
Since people have asked, here is a GitHub page with all of the code used to generate my R function usage analyses: cran-function-usage-analysis.
Abstract Data Type Operations in R
This morning, I got a chance to read enough of the R Language Definition to finish my implementations of push and pop. While I was at it, I also wrote implementations of unshift, shift, queue and dequeue. Here they are: 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 push <- function(vector, item) { vector.lvalue.symbol <- substitute(vector) new.expression <- paste(vector.lvalue.symbol,
R Function Usage Frequencies, Take 2
Yesterday, Hadley Wickham commented on my post on the frequency of calling various R functions that it would be helpful to have the number of packages that call a function in addition to the number of times that the function is called. I compiled the relevant data last night: you can grab it here This
Implementing Push and Pop in R
Having grown up with Perl, there are two functions that I desperately miss while programming in R: push and pop. Continually writing 1 vector <- c(vector, new.entry) tries my patience, while writing 1 2 vector <- rep(NA, inscrutable.constant) vector <- new.entry makes me feel like I’m programming in C, rather than a higher-level programming language. That said, here’s a simplistic hack to provide
R Function Usage Frequencies
A few months ago I decided to apply word frequency analysis ideas to R code. My idea was simple: the functions that one should invest the most effort into learning are precisely those functions that are used most frequently in real world code. In fact, this simple idea can be applied to spoken languages as
The Top Scores for Canabalt, Take 2
Introduction As promised on Thursday, here’s my second pass at a statistical analysis of Canabalt scores. There are some useful results I’ll present right at the start, and then there are some results that are more or less worthless, except that working through my own mistakes helped me to think more clearly about statistical modeling in
Zero Inflated Models and Generalized Linear Mixed Models with R.
Zuur, Saveliev, Ieno (2012).
