451 search results for "KnitR"

A Few Tips for Writing an R Book

June 3, 2013
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A Few Tips for Writing an R Book

I just finished fixing (hopefully all) the problems in the knitr book returned from the copy editor. David Smith has kindly announced this book before I do. I do not have much to say about this book: almost everything in the book can be found in the on...

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Two forthcoming R books

May 29, 2013
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Two forthcoming R books

Today I learned about two forthcoming R books that I'm now looking forward to. The first is Applied Predictive Modeling by Max Kuhn and Kjell Johnson. Max Kuhn is the author of the caret package, an extremely useful and powerful R package for fitting and optimizing all kinds of predictive models in R. It's available now on Amazon Kindle...

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Interactive presentation with slidify and googleVis

May 28, 2013
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Interactive presentation with slidify and googleVis

Last week I was invited to give an introduction to googleVis at Lancaster University. This time I decided to use the R package slidify for my talk. Slidify, like knitr, is built on Markdown and makes it very easy to create beautiful HTML5 presentations...

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Updates to the Social Science Starter Kit

May 27, 2013
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The Emacs Social Science Starter Kit is a drop-in collection of packages and settings for Emacs 24 aimed at people like me: that is, people doing social science data analysis and writing, using some combination of tools like R, git, LaTeX, Pandoc, perh...

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Writing a Minimal Working Example (MWE) in R

May 27, 2013
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Writing a Minimal Working Example (MWE) in R

How to Ask for Help using R How to Ask for Help using R The key to getting good help with an R problem is to provide a minimally working reproducible example (MWRE). Making an MWRE is really easy with R, and it will help ensure that...

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Creating a presence-absence raster from point data

May 27, 2013
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Creating a presence-absence raster from point data

I’m working on generating species distribution models at the moment for a few hundred species. Which means that I’m trying to automate as many steps as possible in R to avoid having to click buttons hundreds of times in ArcView. … Continue reading →

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The R-Podcast Episode 13: Interview with Yihui Xie

May 23, 2013
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It’s an episode of firsts on the R-Podcast! In this episode recorded on location I had the honor and privilege of interviewing Yihui Xie, author of many innovative packages such as knitr and animation. Some of the topics we discussed include: Yihui’s motivation for creating knitr and some key new features How markdown plays a

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Combining dataframes when the columns don’t match

May 13, 2013
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Combining dataframes when the columns don’t match

Most of my work recently has involved downloading large datasets of species occurrences from online databases and attempting to smoodge1 them together to create distribution maps for parts of Australia. Online databases typically have a ridiculous number of columns with … Continue reading →

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Reading an R file from GitHub

Reading an R file from GitHub

Lets say that I want to read in this R file from GitHub into R. The first thing you have to do is locate the raw file. You can do so by clicking on the Raw button in GitHub. In this case it’s https://raw.github.com/lcolladotor/ballgownR-devel/master/ballgownR/R/infoGene.R One would think that using source() would work, but it doesn’t as shown below: source("https://raw.github.com/lcolladotor/ballgownR-devel/master/ballgownR/R/infoGene.R") ##...

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Volatility Regimes: Part 2

Volatility Regimes: Part 2

Adam Duncan from January, 2013Also avilable on R-bloggers.com Strategy Implications In this part of the volatility regimes analysis, we’ll use the regime identification framework established in part 1 to draw conclusions about which strategies work best is each regime. That should prove useful to us and goes a long way to answering the question, “What strategies should I be...

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