## Rcpp annuities

I was tidying up some R code that involved some ‘looping’ and wondered whether the approach I’d taken could be improved upon (it worked and was reasonably fast, so hadn’t bothered refactoring it until now). Essentially it gave me an excuse to finally start exploring Rcpp (in this case, RcppArmadillo). Background is that at work we use a lot of monte carlo simulations through economic scenario generators [https://www.actuaries.org.uk/learn-develop/attend-event/economic-scenario-generators] and so are often dealing with matrices with dimensions representing timesteps (for projecting, for example, interest rates) and simulations. [Read More]

## neo-generalism

A combination of: re-reading a blog by @drob encouraging aspiring data scientists to write a blog, and a desire to have more people where I work writing and communicating technical ideas both to colleagues and externally led me to revisit this site, something I first started about a year ago (I thought I should perhaps practice what I’m preaching). One thing I was struggling with was a name for the site, when I remembered an article titled ‘Rise of the Neo-Generalist’ that I’d come across whilst researching for a talk I had to give (the talk was about future opportunities for actuarial1 skillsets). [Read More]

## Rainfall

I grew up in Fife and now live on the outskirts of Glasgow. And maybe it’s just the ‘lovely’ July weather we’ve been experiencing, or maybe it’s just that I’m getting older and have a selective memory for the past, but I don’t recall summers being quite so wet when I was growing up! I thought I’d take the opportunity to explore the data and play around with some visualisation… [Read More]

## Testing CI of blog

Another brief post in order to test whether the setup for continuous integration through Travis is working properly.

## Trying out blogdown

This is just a quick check to see if I can easily add posts to this blog using blogdown.

With a lack of imagination, I’m using the mtcars data set and ggplot (via tidyverse) to check it’s working ok (using viridis for colours).

library(tidyverse)
library(viridis)
mtcars %>%
ggplot() +
theme_bw() +
geom_point(aes(x = disp, y = hp, colour = mpg)) +
scale_color_viridis() +
facet_wrap(~gear) +
theme(strip.background = element_rect(fill = "transparent"))