Publications by R on mages' blog
Hierarchical compartmental reserving models
Today, I will sketch out ideas from the Hierarchical Compartmental Models for Loss Reserving paper by Jake Morris, which was published in the summer of 2016 (Morris (2016)). Jake’s model is inspired by PK/PD models (pharmacokinetic/pharmacodynamic models) used in the pharmaceutical industry to describe the time course of effect intensity in res...
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PK/PD reserving models
This is a follow-up post on hierarchical compartmental reserving models using PK/PD models. It will show how differential equations can be used with Stan/ brms and how correlation for the same group level terms can be modelled. PK/ PD is usually short for pharmacokinetic/ pharmacodynamic models, but as Eric Novik of Generable pointed out to me, i...
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Insurance Data Science 2018
The abstract submission deadline for the Insurance Data Science conference at Cass Business School on 16 July 2018 is closing soon. You have until the 9th of April to submit your abstract. Please send your abstract to [email protected]. We like to see proposals for talks that demonstrate how data science is used in insurance, e.g. in risk assess...
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Models are about what changes, and what doesn’t
Following on from last week’s post on Principled Bayesian Workflow I want to reflect on how to motivate a model. The purpose of most models is to understand change, and yet, considering what doesn’t change and should be kept constant can be equally important. I will go through a couple of models in this post to illustrate this ide...
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Notes from the 1st Insurance Data Science event
The first Insurance Data Science event was held at Cass Business School last week, 16 – 17 July 2018. The conference followed on from five iterations of the R in Insurance events, which have the aim of bringing together practitioners and academics together to discuss and exchange ideas and needs in the sector. Expanding the remit fr...
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Use domain knowledge to review prior distributions
At the Insurance Data Science conference, both Eric Novik and Paul-Christian Bürkner emphasised in their talks the value of thinking about the data generating process when building Bayesian statistical models. It is also a key step in Michael Betancourt’s Principled Bayesian Workflow. In this post, I will discuss in more detail how...
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