1042 search results for "LaTex"

In praise of ProjectTemplate for reproducible research

September 7, 2012
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In praise of ProjectTemplate for reproducible research

As you might know from some of my previous posts, I’m a big fan of making my scientific work reproducible. My main reasons for being so keen on this are: 1. Reproducibility is key to science – if it can’t be reproduced then it can not be verified (that is, the experiment can’t be tried again

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RStudio is RStupendous

September 3, 2012
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I am a sucker for beautiful applications (like the ggplot2 web tool mentioned here). The latest R-related application to catch my eye is RStudio. RStudio™ is a free and open source integrated development environment (IDE) for R. You can run it on your desktop (Windows, Mac, or Linux) or even over the web using RStudio

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Heatmap tables with ggplot2, sort-of

August 27, 2012
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Heatmap tables with ggplot2, sort-of

I wrote before about heatmap tables as a better way of producing frequency or other tables, with a solution which works nicely in latex. It is possible to do them much more easily in ggplot2, like this library(Hmisc) library(ggplot2) library(reshape) data(HairEyeColor) P=t(HairEyeColor) Pm=melt(P) ggfluctuation(Pm,type="heatmap")+geom_text(aes(label=Pm$value),colour="white")+ opts(axis.text.x=theme_text(size = 15),axis.text.y=theme_text(size = 15)) Note that ggfluctuation will also take

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Custom CSS for HTML generated using RStudio

August 26, 2012
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Custom CSS for HTML generated using RStudio

People have been telling me for a while that the latest version of RStudio, the IDE for R, is a great way to generate reports. I finally got around to trying it out and for once, the hype is justified. Start with this excellent tutorial from Jeremy Anglim. Briefly: the process is not so different

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Creating beautiful reports from R with knitr

August 21, 2012
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Creating beautiful reports from R with knitr

People use the R language every day to create the elements of reports: tables, charts, analyses, and forecasts. But assembling all of that information into a print-ready document laid out with text can a hassle. You can cut-and-paste all of the elements into Word, but then what do you do when the data file gets updated at the last...

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Mid-August flotsam

August 20, 2012
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Mid-August flotsam

Reached mid-semester point, with quite a few new lectures to prepare. Nothing extremely complicated but, as always, the tricky part is finding a way to make it meaningful and memorable. Sometimes, and this is one of those times, I sound … Continue reading →

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Heatmap tables with ggplot2

August 20, 2012
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Heatmap tables with ggplot2

I wrote before about heatmap tables as a better way of producing frequency or other tables, with a solution which works nicely in latex. It is possible to do them much more easily in ggplot2, like this library(Hmisc) library(ggplot2) library(reshape) data(HairEyeColor) P=t(HairEyeColor) Pm=melt(P) ggfluctuation(Pm,type="heatmap")+geom_text(aes(label=Pm$value),colour="white")+ opts(axis.text.x=theme_text(size = 15),axis.text.y=theme_text(size = 15)) Note that ggfluctuation will also take … Continue reading...

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The Setup (Part 1)

August 16, 2012
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The Setup (Part 1)

One of the more challenging things about beginning graduate school was learning what tools and software I needed in order to work efficiently. Unlike college where software requirements were laid out in front of me and everyone seemed to use … Continue reading →

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Probit Models with Endogeneity

August 15, 2012
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Probit Models with Endogeneity

Dealing with endogeneity in a binary dependent variable model requires more consideration than the simpler continuous dependent variable case. For some, the best approach to this problem is to use the same methodology used in the continuous case, i.e. 2 stage least squares. Thus, the equation of interest becomes a linear probability model (LPM). The

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The fanplot package for R

August 13, 2012
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The fanplot package for R

My fanplot package has gone up on CRAN. Here is a online version of the vignette. Introduction The fanplot package contains a collection of R (R Development Core Team, 2012) functions to effectively display plots of sequential distributions such as … Continue reading →

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