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QuantLib now included as part of Ceemple, a rapid JIT based C++ technical coputing environment. Available (free) from http://www.ceemple.com.


I use both R and Matlab. In my experience Matlab is often more convenient for optimization problems. For example the excellent convex optimization software cvx is written in Matlab. There are also quite a few quants who publish their code in Matlab. Also debugging in R can be painful - I like R apart from these quibbles.


For Windows - Parallel processing and GPU computing - are two areas. R has numerous packages for parallel processing but all of them require you to replicate the whole environment for each worker which massively degrades the performance of parallel processing and in most real life cases, there is almost no speed up because of the reduced memory available to ...


the main thing that R is lacking is the proper help and product documentation in comparison to Stata, Matlab, SAS and similar commercial software. there's a package called OxMetrics, which has an interesting algebraic approach to model specification and scripting. it's hard to explain, but when you use it, it saves a lot of time, because it automates a ...

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