Monthly Archives: November 2010

R.I.P. StatProb?

November 22, 2010
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R.I.P. StatProb?

As posted in early August from JSM 2010 in Vancouver, StatProb was launched as a way to promote an on-line encyclopedia/wiki with the scientific backup of expert reviewers. This was completely novel and I was quite excited to take part in the venture as a representative of the Royal Statistical Society. Most unfortunately, the separation

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Access the InfoChimps API from R

November 22, 2010
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InfoChimps.com is mainly known as a clearinghouse for finding large data sets, for free or for sale. But they have also released (in beta, at least) an API that lets you find some pretty useful information on-demand. Normally, you'd have you use RESTful calls to access the API, but now Drew Conway has created an R package (and released...

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Example 8.15: Firth logistic regression

November 22, 2010
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Example 8.15: Firth logistic regression

In logistic regression, when the outcome has low (or high) prevalence, or when there are several interacted categorical predictors, it can happen that for some combination of the predictors, all the observations have the same event status. A similar e...

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Homage to floating points

November 22, 2010
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I recently got very close to the floating point trap, again, so here is a little tribute with some small examples!

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Retrieving transcriptome sequences for RNASeq analysis

November 22, 2010
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One approach for analyzing RNASeq data from an organism with a well-annotated genome, is to align the reads to mRNA (cDNA) sequences instead of the genome. To do that you need to extract the transcript sequences from a database. This is how to extract ensembl transcript sequences from UCSC from within R:_________________________________________________ library(GenomicFeatures) library(BSgenome.Hsapiens.UCSC.hg18) tr tr_seq write.XStringSet(tr_seq, file="hg18.ensgene.transcripts.fasta", 'fasta', width=80, append=F) _________________________________________________ Next steps...

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Retrieving transcriptome sequences for RNASeq analysis

November 22, 2010
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One approach for analyzing RNASeq data from an organism with a well-annotated genome, is to align the reads to mRNA (cDNA) sequences instead of the genome. To do that you need to extract the transcript sequences from a database. This is how to extract ensembl transcript sequences from UCSC from within R:_________________________________________________ library(GenomicFeatures) library(BSgenome.Hsapiens.UCSC.hg18) tr tr_seq write.XStringSet(tr_seq, file="hg18.ensgene.transcripts.fasta", 'fasta', width=80, append=F) _________________________________________________ Next steps...

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Were stock returns really better in 2007 than 2008?

November 22, 2010
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Were stock returns really better in 2007 than 2008?

We know that the S&P 500 was up a little in 2007 and down a lot in 2008.  So on the surface the question seems really stupid.  But randomness played a part.  Let’s have a go at deciding how much of a part. Figure 1: Comparison of 2007 and 2008 for the S&P 500. Statistical … Continue reading...

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Graphical comparison of MCMC performance [arXiv:1011.445]

November 22, 2010
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Graphical comparison of MCMC performance [arXiv:1011.445]

A new posting on arXiv by Madeleine Thompson on a graphical tool for assessing performance. She has developed a software called SamplerCompare, implemented in R and C. The graphical evaluation plots “log density evaluations per iteration times autocorrelation time against a tuning parameter in a grid of plots where rows represent distributions and columns represent

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Animate .gif images in R / ImageMagick

November 21, 2010
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Animate .gif images in R / ImageMagick

Yesterday I surfed the web looking for 3D wireframe examples to explain linear models in class. I stumbled across this site where animated 3D wireframe plots are outputted by SAS.  Below I did something similar in R. This post shows the few steps of how to create an animated .gif file using R and ImageMagick.

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My First R Package: infochimps

November 20, 2010
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I have finally taken the plunge and created my first R package! As frequent readers will know, I often sing the praises of infochimps, a startup out of Austin, TX attempting to be the world’s data clearinghouse. While infochimps is an excellent resource for data sets, they also provide their own set excellent data

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