Monthly Archives: November 2013

Analyzing baseball data with R

November 27, 2013
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Analyzing baseball data with R

This week, the post is an interview with Max Marchi. Max is the author, with Jim Albert, of the book "Analyzing baseball data with R". Hi, Max. Welcome back to MilanoR. Last time you wrote for us a series of … Continue reading →

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The R Backpages 2

November 27, 2013
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The R Backpages 2

by Joseph Rickert In this roundup of R-related news: Domino enables data science collaboration; Plotly adds an R graphics gallery; Revolution Analytics R user group sponsorship applications are open; and Quandl adds new data sets. San Francisco startup takes on collaborative Data Science Domino, a San Francisco based startup, is inviting users to sign up to beta test its...

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Mapping Power Outages In Maine With R

November 27, 2013
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Mapping Power Outages In Maine With R

UPDATE: A Shiny (dynamic) version of this is now available. We had yet-another power outage this morning due to the weird weather patterns of the week and it was the final catalyst I needed to crank out some R code to map the affected counties. Central Maine Power provides an outage portal where folks can

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Winter Solstice Survival Guide 2013

November 27, 2013
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Winter Solstice Survival Guide 2013

’tis the season to consume! But for this part of the year, as the Winter Solstice approaches, we consume not for ourselves, but for others, and that’s generally a good thing. Each year we here at Science… sort of like to put together a list of suggestions for the science-inclined in your life. Whether you’re looking

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Five ways to handle Big Data in R

November 27, 2013
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Five ways to handle Big Data in R

Big data was one of the biggest topics on this year’s useR conference in Albacete and it is definitely one of today’s hottest buzzwords. But what defines “Big Data”? And on the practical side: How can big data be tackled in R? What data is big? Hadley Wickham, one of the best known R developers,

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Continuous Integration with OpenCPU

November 27, 2013
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Continuous Integration with OpenCPU

Starting version 1.0.7, the OpenCPU cloud server adds support for continuous integration (CI). This means that Github repositories can be configured to automatically install your package on an OpenCPU server, every time a commit is pushed. To t...

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Continuous Integration with OpenCPU

November 27, 2013
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Continuous Integration with OpenCPU

Starting version 1.0.7, the OpenCPU cloud server adds support for continuous integration (CI). This means that Github repositories can be configured to automatically install your package on an OpenCPU server, every time a commit is pushed. To t...

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Importance sampling schemes for evidence approximation in mixture models

November 26, 2013
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Importance sampling schemes for evidence approximation in mixture models

Jeong Eun (Kate) Lee and I completed this paper, “Importance sampling schemes for evidence approximation in mixture models“, now posted on arXiv. (With the customary one-day lag for posting, making me bemoan the days of yore when arXiv would give a definitive arXiv number at the time of submission.) Kate came twice to Paris in the past

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The little non-informative prior that could (be informative)

November 26, 2013
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The little non-informative prior that could (be informative)

Christian Robert reviewed on line a paper that was critical of non-informative priors. Among the points that were discussed by him and other contributors (e.g. Keith O’Rourke), was the issue of induced priors, i.e. priors which arise from a transformation of original parameters, or of observables. I found this exchange interesting because I did something

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New R package raincpc: Obtain and Analyze Rainfall data from the Climate Prediction Center (CPC)

November 26, 2013
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The Climate Prediction Center's (CPC) daily rainfall data for the entire world, 1979 - present & 50-km resolution, is one of the few high quality and long term observation-based rainfall products. Data is available at CPC's ftp site. However, it is...

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