Publications by Markus Gesmann
ChainLadder 0.2.1 released
Over the weekend we released version 0.2.1 of the ChainLadder package for claims reserving on CRAN. New FeaturesNew function PaidIncurredChain by Fabio Concina, based on the 2010 Merz & Wüthrich paper Paid-incurred chain claims reserving methodFunctions plot.MackChainLadder and plot.BootChainLadder gained new argument which, allowing...
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Notes from the 3rd R in Insurance Conference
Photo: Arthur CharpentierThe R in Insurance conference in Amsterdam was a sold out success! Congratulations to the organising committee at the University of Amsterdam, and many thanks to our sponsors:Milliman, RStudio, CYBAEA, Deloitte, a.s.r., Triple A Risk Finance, AEGON, Delta Lloyd Amsterdam, QBE Re and APPLIED AIThis one-day conference focus...
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Generalised Linear Models in R
Linear models are the bread and butter of statistics, but there is a lot more to it than taking a ruler and drawing a line through a couple of points. Some time ago Rasmus Bååth published an insightful blog article about how such models could be described from a distribution centric point of view, instead of the classic error term...
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Visualising theoretical distributions of GLMs
Two weeks ago I discussed various linear and generalised linear models in R using ice cream sales statistics. The data showed not surprisingly that more ice cream was sold at higher temperatures.icecream <- data.frame( temp=c(11.9, 14.2, 15.2, 16.4, 17.2, 18.1, 18.5, 19.4, 22.1, 22.6, 23.4, 25.1), units=c(185L, 215L, 332...
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Visualising the predictive distribution of a log-transformed linear model
Last week I presented visualisations of theoretical distributions that predict ice cream sales statistics based on linear and generalised linear models, which I introduced in an earlier post.Theoretical distributionsToday I will take a closer look at the log-transformed linear model and use Stan/rstan, not only to model the sales statistics, but ...
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Bayesian regression models using Stan in R
It seems the summer is coming to end in London, so I shall take a final look at my ice cream data that I have been playing around with to predict sales statistics based on temperature for the last couple of weeks [1], [2], [3].Here I will use the new brms (GitHub, CRAN) package by Paul-Christian Bürkner to derive the 95% prediction c...
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Next Kölner R User Meeting: Friday, 18 September 2015
The 15th Cologne R user group meeting is scheduled for this Friday, 18 September 2015 and we have a full agenda with three talks followed by networking drinks. R in big data pipeline with luigi (Yuki Katoh)R in big data pipeline: Put your awesome R codes into production. Learn how to build solid big data pipeline around it. shinyjs (Paul Viefer...
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Notes from the Kölner R meeting, 18 September 2015
Last Friday the Cologne R user group came together for the 15th time. Since its inception over three years ago the group evolved from a small gathering in a pub into an active data science community, covering wider topics than just R. Still, R is the link and clue between the different interests. Last Friday’s agenda was a good exam...
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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. However, th...
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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 ...
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