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MAGES' BLOG
Markus Gesmann. About me. I am a mathematician, working in the insurance and capital markets. I am also the maintainer and co-author of the ChainLadder and googleVis packages and founder of the Bayesian Mixer Meetups and Insurance Data Science conference series. In my spare time, I write this blog on data analysis related topics. KALMAN FILTER EXAMPLE VISUALISED WITH R At the last Cologne R user meeting Holger Zien gave a great introduction to dynamic linear models (dlm). One special case of a dlm is the Kalman filter, which I will discuss in this post in more detail. I kind of used it earlier when I measured the temperature with my Arduino at home. Over the last week I came across the wonderful quantitative economic modelling site quant-econ.net, designed LOGISTIC MAP: FEIGENBAUM DIAGRAM IN R The other day I found some old basic code I had written about 15 years ago on a Mac Classic II to plot the Feigenbaum diagram for the logistic map. I remember, it took the little computer the whole night to produce the bifurcation chart. With today’s computers even a for-loop in a scripting language like R takes only a few seconds. logistic.map f scan(f, n=1) Read 1 FIRST STEPS WITH CHAINLADDER: IMPORT TRIANGLE FROM EXCEL How do you get the triangle into R and execute a reserving function, such as MackChainLadder?. Well, there are many ways to do this and the ChainLadder package vignette, as well as the R manual on Data Import/Export has all of the details, but here is a quick and dirty solution using a CSV-file.. Open a new Excel workbook and copy your triangle into cell A1, with the first column being HIGH RESOLUTION GRAPHICS WITH R For most purposes PDF or other vector graphic formats such as windows metafile and SVG work just fine. However, if I plot lots of points, say 100k, then those files can get quite large and bitmap formats like PNG can be the better option. I just have to be mindful of the resolution. As an example I create the following plot: xDetails
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