Blog Archives

Flowing triangles

January 26, 2016
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Flowing triangles

I have admired the work of the artist Bridget Riley for a long time. She is now in her eighties, but as it seems still very creative and productive. Some of her recent work combines simple triangles in fascinating compositions. The longer I look at them, the more patterns I recognise. Yet, the actual painting can be...

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Formatting table output in R

January 19, 2016
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Formatting table output in R

Formatting data for output in a table can be a bit of a pain in R. The package formattable by Kun Ren and Kenton Russell provides some intuitive functions to create good looking tables for the R console or HTML quickly. The package home page demonstrates the functions with illustrative examples nicely.There are a few points I...

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R in Insurance: Registration and abstract submission opened

January 12, 2016
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R in Insurance: Registration and abstract submission opened

Following the successful 3rd R in Insurance conference in Amsterdam last year, we return to London this year.The registration for the 4th conference on R in Insurance on Monday 11 July 2016 at Cass Business School has opened. This one-day conference will focus again on applications in insurance and actuarial science that...

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Next Kölner R User Meeting: Friday, 4 December 2015

December 3, 2015
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Next Kölner R User Meeting: Friday, 4 December 2015

The 16th Cologne R user group meeting is scheduled for this Friday, 4 December 2015 and we have great line up with three talks followed by networking drinks. Monitoring process change using Bayesian methods (Mick Cooney)A common business problem is to evaluate the effect of a change of process, and this talk...

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Notes from Warsaw R meetup

December 1, 2015
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Notes from Warsaw R meetup

I had the great pleasure time to attend the Warsaw R meetup last Thursday. The organisers Olga Mierzwa and Przemyslaw Biecek had put together an event with a focus on R in Insurance (btw, there is a conference with the same name), discussing examples of pricing and reserving in general and life insurance.Experience vs. DataI...

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Hierarchical Loss Reserving with Stan

November 10, 2015
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Hierarchical Loss Reserving with Stan

I continue with the growth curve model for loss reserving from last week's post. Today, following the ideas of James Guszcza I will add an hierarchical component to the model, by treating the ultimate loss cost of an accident year as a random effect. Initially, I will use the nlme R package, just as James did...

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Loss Developments via Growth Curves and Stan

November 3, 2015
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Loss Developments via Growth Curves and Stan

Last week I posted a biological example of fitting a non-linear growth curve with Stan/RStan. Today, I want to apply a similar approach to insurance data using ideas by David Clark and James Guszcza .Instead of predicting the growth of dugongs (sea cows), I would like to predict the growth of cumulative insurance...

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Non-linear growth curves with Stan

October 27, 2015
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Non-linear growth curves with Stan

I suppose the go to tool for fitting non-linear models in R is nls of the stats package. In this post I will show an alternative approach with Stan/RStan, as illustrated in the example, Dugongs: "nonlinear growth curve", that is part of Stan's documentation. The original example itself is taken from OpenBUGS. The data describes the...

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R in Insurance 2016

October 6, 2015
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R in Insurance 2016

Following the successful 3rd R in Insurance conference in Amsterdam this year, we will return to London next year. We will be back at Cass Business School, 11 July 2016.The event will focus again on the use of R in insurance, bringing together experts from industry and academia with a diverse background...

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ChainLadder 0.2.2 is out with improved glmReserve function

September 29, 2015
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ChainLadder 0.2.2 is out with improved glmReserve function

We released version 0.2.2 of ChainLadder a few weeks ago. This version adds back the functionality to estimate the index parameter for the compound Poisson model in glmReserve using the cplm package by Wayne Zhang. Ok, what does this all mean? I will run through a couple of examples and look behind the scene of glmReserve....

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