This post describes how to pass external arguments to R when calling a Rscript with a command line. The case study presented here is very simple: a Rscript is called which needs, as an input, a file name (a text file containing data which are loaded into R to be processed) and which can also accept an optional additional argument (an output file name: if this argument is not provided, the program supplies one by default).
I’ve covered the Anti-shipping Activity Messages (ASAM) Database before for TLAPD before but getting, updating and working with the data has more pain points than it should, so I wrapped a small package around it.
In my last post I talked about how this question on Cross-Validated got me interested. Basically the challenge is to compare two data generating models to see if they are essentially the same. Since then I’ve noticed that this problem comes up in a number of other contexts too.
The code snippet below creates the above graphic …
In the previous post, I went through a simple exercise which, to me, clearly demonsrtates that 60% out of sample guess rate (on daily basis) for S&P 500 will generate ridiculous returns. From the feedback I got, it seemed that my example was somewhat unconvincing. Let’s dig a bit further then.
The business problem tackled here is trying to improve customer service for YourCabs, a cab company in Bangalore. The problem of interest is booking cancellations by the company due to unavailability of a car. The challenge is that cancellations can occur very close to the trip start time, thereby causing passengers inconvenience.
We show an example of how to ‘sort’ high dimensional objects using PCA, specifically we answer ‘how can we sort colours?’ This screencast presents an scalable algorithm, based on PCA, to sort colours unsupervised.