Posts Tagged ‘ Rstats ’

Calling R from Scala sbt projects

January 24, 2015
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Calling R from Scala sbt projects

Overview In previous posts I’ve shown how the jvmr CRAN R package can be used to call Scala sbt projects from R and inline Scala Breeze code in R. In this post I will show how to call to R from a Scala sbt project. This requires that R and the jvmr CRAN R package […]

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Inlining Scala Breeze code in R using jvmr and sbt

January 3, 2015
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Inlining Scala Breeze code in R using jvmr and sbt

Introduction In the previous post I showed how to call Scala code from R using sbt and jvmr. The approach described in that post is the one I would recommend for any non-trivial piece of Scala code – mixing up code from different languages in the same source code file is not a good strategy […]

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Calling Scala code from R using jvmr

January 2, 2015
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Calling Scala code from R using jvmr

Introduction In previous posts I have explained why I think that Scala is a good language to use for statistical computing and data science. Despite this, R is very convenient for simple exploratory data analysis and visualisation – currently more convenient than Scala. I explained in my recent talk at the RSS what (relatively straightforward) […]

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One-way ANOVA with fixed and random effects from a Bayesian perspective

December 22, 2014
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One-way ANOVA with fixed and random effects from a Bayesian perspective

This blog post is derived from a computer practical session that I ran as part of my new course on Statistics for Big Data, previously discussed. This course covered a lot of material very quickly. In particular, I deferred introducing notions of hierarchical modelling until the Bayesian part of the course, where I feel it […]

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R resources

December 3, 2014
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This is the third in my weekly series of posts pointing out resources on this site. This week’s topic is R. R language for programmers Default arguments and lazy evaluation in R Distributions in R Moving data between R and Excel via the clipboard Sweave: First steps toward reproducible analyses Troubleshooting Sweave Regular expressions in […]

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Statistical computing languages at the RSS

November 22, 2014
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Statistical computing languages at the RSS

On Friday the Royal Statistical Society hosted a meeting on Statistical computing languages, organised by my colleague Colin Gillespie. Four languages were presented at the meeting: Python, Scala, Matlab and Julia. I presented the talk on Scala. The slides I presented are available, in addition to the code examples and instructions on how to run […]

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Statistics for Big Data

November 22, 2014
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Statistics for Big Data

Doctoral programme in cloud computing for big data I’ve spent much of this year working to establish our new EPSRC Centre for Doctoral Training in Cloud Computing for Big Data, which partly explains the lack of posts on this blog in recent months. The CDT is now established, with 11 students in the first cohort, […]

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One datavis for you, ten for me

September 14, 2014
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One datavis for you, ten for me

Over the years of my graduate studies I made a lot of plots. I mean tonnes. To get an extremely conservative estimate I grep’ed for every instance of “plot\(” in all of the many R scripts I wrote over the past five years. The actual number is very likely orders of magnitude larger as 1) many […]

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Plot with ggplot2, interact, collaborate, and share online

July 31, 2014
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Plot with ggplot2, interact, collaborate, and share online

Editor’s note: This is a guest post by Marianne Corvellec from Plotly. This post is based on an interactive Notebook (click to view) she presented at the R User Conference on July 1st, 2014. Plotly is a platform for making, editing, and sharing graphs. If you are used to making plots with ggplot2, you can […]

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Tuning particle MCMC algorithms

June 8, 2014
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Tuning particle MCMC algorithms

Several papers have appeared recently discussing the issue of how to tune the number of particles used in the particle filter within a particle MCMC algorithm such as particle marginal Metropolis Hastings (PMMH). Three such papers are: Doucet, Arnaud, Michael Pitt, and Robert Kohn. Efficient implementation of Markov chain Monte Carlo when using an unbiased […]

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