Posts Tagged ‘ Rstats ’

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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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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Online R and Plotly Graphs: Canadian and U.S. Maps, Old Faithful with Multiple Axes, & Overlaid Histograms

February 6, 2014
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Online R and Plotly Graphs: Canadian and U.S. Maps, Old Faithful with Multiple Axes, & Overlaid Histograms

Guest post by Matt Sundquist of plot.ly. Plotly is a social graphing and analytics platform. Plotly’s R library lets you make and share publication-quality graphs online. Your work belongs to you, you control privacy and sharing, and public use is free (like GitHub). We are in beta, and would love your feedback, thoughts, and advice. […]

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What’s Warren Buffett’s $1 Billion Basketball Bet Worth?

January 23, 2014
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What’s Warren Buffett’s $1 Billion Basketball Bet Worth?

A friend of mine just alerted me to a story on NPR describing a prize on offer from Warren Buffett and Quicken Loans. The prize is a billion dollars (1B USD) for correctly predicting all 63 games in the men’s Division I college basketball tournament this March. The facebook page announcing the contest puts the odds at 1:9,223,372,036,854,775,808, […]

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Simudidactic

November 23, 2013
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Simudidactic

auto·di·dact n. A self-taught person. From Greek autodidaktos, self-taught : auto-, auto- + didaktos, taught; + sim·u·late v. To create a representation or model of (a physical system or particular situation, for example). From Latin simulre, simult-, from similis, like; = (If you can get past the mixing of Latin and Greek roots) sim·u·di·dactic adj. To learn by creating a representation or model of a physical system or […]

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