Monthly Archives: October 2010

Bayesian Diabetes Projections by CDC

October 22, 2010
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Bayesian Diabetes Projections by CDC

Bayesian methods are supporting decisions and news at the national level! The Centers for Disease Control and Prevention summarizes a report published in the journal Population Health Metrics. The news also made it to the national media. The report (JP Boyle, TJ Thompson, EW Gregg, LE Barker, and DF Williamson (2010) “Projection of the year

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Help! My model fits too well!

October 22, 2010
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Help! My model fits too well!

This is sort-of related to my sidelined study of graph algebra. I was thinking about data I could apply a first-order linear difference model to, and the stock market came to mind. After all, despite some black swan sized shocks, what better predicts a day’s closing than the previous day’s closing? So,

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Because it’s Friday: Arthur C Clarke predicts the present

October 22, 2010
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On the BBC Horizon programme in 1964, Arthur C Clarke made some predictions about the future. He prefaced his predictions with the following caveat: If, by some miracle, a prophet could describe the future exactly as it was going to take place, his predictions would sound so absurd, so farfetched, that everybody would laugh him to scorn. So what...

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Incremental improvements to Nightlights mapping thanks to R-Bloggers

October 22, 2010
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Incremental improvements to Nightlights mapping thanks to R-Bloggers

The R community is very generous and collaborative. This post walks through the suggestions left by commenters to my previous post on Steve Mosher's Nightlights work, and show the resulting much-improved output.

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A workflow for R

October 22, 2010
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Writing an R script is one thing. Organizing your process: where to put the data, how to refer to files in scripts, how to run the scripts, and how to produce and collect and report the results; that's quite another. Every R user has their own workflow for doing data analysis with R, but the best workflows achieve the...

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Creating even NICER, publishable, embeddable plots using tikzDevice in R for use with LaTeX

October 22, 2010
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Creating even NICER, publishable, embeddable plots using tikzDevice in R for use with LaTeX

It’s true. I like to do my work in R and write using LaTeX (well, I prefer to use org-mode for less formal writing and/or if I don’t have to typeset a lot of math). I haven’t done a lot of LaTeX’ing or Sweaving in the last year since 1) I’ve been collaborating with scientists... Read more »

For a wider use of R

October 22, 2010
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Two things that are crucial for a wider use of R among applied researchers. The first one is data manipulation/reshaping tool. I think the package "reshape" and "reshape2" have done good job and have largely removed the barrier. The second one is ...

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For a wider use of R

October 22, 2010
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Two things that are crucial for a wider use of R among applied researchers. The first one is data manipulation/reshaping tool. I think the package "reshape" and "reshape2" have done good job and have largely removed the barrier. The second one is ...

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How to avoid annoying a referee

October 22, 2010
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It’s not a good idea to annoy the referees of your paper. They make recommendations to the editor about your work and it is best to keep them happy. There is an interesting discussion on stats.stackexchange.com on this subject. This inspired my own list below. Explain what you’ve done clearly, avoiding unnecessary jargon. Don’t claim

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abc

October 21, 2010
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abc

Michael Blum and Olivier François, along with Katalin Csillery, just released an R package entitled abc. (I am surprised the name was not already registered!) Its aim is obviously to implement ABC approximations for Bayesian inference: Description The ’abc’ package provides various functions for parameter estimation and model selection in an ABC framework. Three main

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