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Darren Wilkinson's blog Statistics, computing, functional programming, data science, Bayes, stochastic modelling, systems biology and bioinformatics Menu and widgets Functional programming (FP) languages are great for statistical computing, computational statistics, and machine learning. They are particularly well-suited to scalable computation, where this could either mean scaling up to distribut
Darren Wilkinson's blog Statistics, computing, functional programming, data science, Bayes, stochastic modelling, systems biology and bioinformatics Menu and widgets Introduction In the previous post I outlined why I think Scala is a good language for statistical computing and data science. In this post I want to give a quick taste of Scala and the Breeze numerical library to whet the appetite of
Darren Wilkinson's blog Statistics, computing, functional programming, data science, Bayes, stochastic modelling, systems biology and bioinformatics Menu and widgets Introduction Regular readers of this blog will know that in April 2010 I published a short post showing how a trivial bivariate Gibbs sampler could be implemented in the four languages that I use most often these days (R, python, C, J
Darren Wilkinson's blog Statistics, computing, functional programming, data science, Bayes, stochastic modelling, systems biology and bioinformatics Menu and widgets In the previous post I gave a quick introduction to the CRAN R package smfsb, and how it can be used for simulation of Markov processes determined by stochastic kinetic networks. In this post I’ll show how to use data and particle MCM
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