I recently worked on a fun project at work. I developed a web-interface for administering a questionnaire using the Delphi method. The Delphi method aims to bring consensus on a given topic using a concept similar to ‘the wisdom of crowds‘.
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This post is an update on the previous post translating Byron and Wattenberg’s streamgraphs algorithm into R. Byron and Wattenberg’s algorithm produces beautiful streamgraphs with the synthetic data produced by their streams generator. However, the implementation yields an ugly streamgraph when applied to data which might not be as wiggly as the synthetic ones. In the attempts I made I got very peaky wiggles, not smoothed and irregular. In short the graphs did not transmit the idea of a stream, but of a blurry blob or a peaky primitive bat (the wooden club, not the animal, that would be cool!). In this post I bring-up some points to bear in mind when producing a streamgraph. Continue reading “Streamgraph in R [final]”
This is the third post on streamgraph in R. After a simple introduction on how to generate a streamgraphs and an example with actual data it was time for a more general implementation to the creation streamgraphs using R. Continue reading “Streamgraphs in base::R [e.III]”
This posts on multiple mediation on lavaan supplements the two previous ones (1 – introducing multiple mediator analysis with lavaan and 2 – showing an example analysis) by describing how to process lavaan’s output graphically. I discovered the handy package semPlot and I am very positive about it. I will make the example as reproducible as possible, so that each step can be repeated. Also, I am going to try to provide more explanation about the R commands I used because a friend pointed out that the description of the steps was sometimes a bit dry and abstract.
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Until recently I did not have a practical application in which to use streamgraphs. In fact, I still find the visualisation complex to understand, abstract and a bit too artistic. While I recognise that the strength of streamgraphs is the display of all the time series’ values into one (possibly interactive) plot, the amount of data displayed is massive, with many streams and even more data points. Because of the amount of data displayed Continue reading “Streamgraphs in base::R [e.II]”
I always wanted to experiment with parallel computing and multi threading. However, when and how to use parallel computing has always been a bit difficult to conceptualize for me. Until I discovered forking. Here I will describe a simple implementation of fork using the chrono Time c++ library to time the forked processes.
Continue reading “A simple fork example timed with chrono”