Publications by PirateGrunt

Vectors of S4 classes with non-trivial slots

22.07.2013

Here’s another rabbit hole where I spent a bit of time this evening. I like OOP and I like the way R uses vectors. I’ve created a few classes and had started to code a function which would plot a set of them. It all seemed straightforward until I realized that the infrastructure for treating your own classes is something that you have to buil...

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PirateGrunt goes to the CLRS

16.09.2013

Yesterday, I had the great pleasure to speak about using R for loss reserving at the Casualty Loss Reserving Seminar in Boston. My time was spent talking about MRMR, an R package that I’ve created. Version 0.1.2 is now on CRAN, but as there are a couple of bugs, I’d suggest waiting until version 0.1.3 is released. This should happen in a week...

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MRMR on CRAN

27.09.2013

MRMR version 0.1.3 is now available on CRAN. This is (almost) the same version that was discussed at the CLRS two weeks ago. MRMR – Multivariate Regression Models for Reserving- is a tool for non-life actuaries to estimate liability reserves. The emphasis is on exploratory data analysis, visualization and model diagnostics. At present, the fram...

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PirateGruntTV

01.10.2013

I’m on record as being a big fan of Coursera and have wanted to try and create my own video content ever since I saw theirs. Obviously they’re much better at it than I am, both in terms of production quality and content. Still, there probably isn’t much call for actuarial lectures on their site and it’s not so easy to get on the docket at...

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Hurricanes and Reproducible Research

08.11.2013

On vacation with my family this week and that means I have a few minutes now and again to read. One of the books I brought along is Christopher Gandrud’s excellent “Reproducible Research with R and RStudio”. Looking for some data as a test project, I latched onto Hurricane data. Folly Beach was hit pretty hard by hurricane Hugo in 1989. It�...

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Hurricanes in South Carolina

10.11.2013

In a recent post, I discussed the occurrence of hurricanes in the North Atlantic basin. The data comes from the National Oceanic and Atmospheric Association, a member of the US federal government. The data spans a bit more than 150 years. In that post, I make the observation that the data supports a model wherein decade is a meaningful predictor ...

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24 Days of R: Day 1

01.12.2013

Last year, the good people at is.R() spent December publishing an R advent calendar. This meant that for 24 days, every day, there was an interesting post featuring analysis and some excellent visualizations in R. I think it's an interesting (if very challenging) exercise and I'm going to try to do it myself this year. is.R() has been fairly quiet...

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24 Days of R: Day 2

02.12.2013

Need a Hanukkah or Christmas gift for an R analyst? You could do loads worse than Applied Spatial Data Analysis with R by Bivand, Pebesma and Gomez-Rubio. I don't have my copy yet- I'm still working through all of the other books I've bought this year- but I'll likely pick it up sometime early in 2014. Why? Because I love maps. I also love the sp...

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24 Days of R: Day 3

03.12.2013

This is the post where we begin to talk about Michael Caine. There's no strong reason for this. It's not as though I have a great fascination with him. Don't get me wrong, I think he's a fine actor. Michael Caine happened to cross my mind a couple weeks ago when I was listening to an interview with Steven Coogan. He did his fantastic impression of...

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24 Days of R: Day 4

04.12.2013

So my first attempt to sort out the career of Michael Caine via parsing of HTML data was a wash. I'm going to try this again, using Wikipedia. They've got a nice, easy list of his films in an HTML table. Reading an HTML table into R is incredibly easy. The XML library has a function to sort that out. library(XML) URL = "http://en.wikipedia.org/w...

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