Markdown for Manuscripts: Enhancements

Today was my first time using markdown for a manuscript methods section (see previous post on getting set up in markdown). It had lots of equations so using LaTeX to write the equations was quite nice. Here’s an example of the markdown code: \\[ \mu_{s,h,d,y} = \left\{ \begin{array}{1 1} \omega_{s,h,d,y} + \delta_{s}(t_{s,h,d-1,y} – \omega_{s,h,d-1,y}) &…

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Year in Review: 2014

This year has flown by. I can’t believe it will be 2015 before the week is over. Overall, 2014 was a good year. I published 2 papers, have 2 in press, and 2 more in review. The two published papers have already received 3 citations each with only 1 of the 6 being a self…

Writing Scientific Papers Using Markdown

Writing Scientific Papers Using Markdown Markdown is a markup language that is very handy and easy to use. I won’t say much more about it, but I’ve written about it before here and here. I’ve used it increasingly for writing blog posts, webpages, taking notes, with GitHub issue tracking, and with R code (R Markdown…

Lags and Moving Means in dplyr

I’ve been a big fan of dplyr from the start. While learning any new package can be frustrating, overall dplyr is fast and consistent. The Nonstandard Evaluation (see vignette(“nse”) for details) is both a blessing and a curse, overall dply is making life with big(ish) data much easier. The rapid development makes it a challenge…

dplyr is great…but

I have been loving Hadley Wickham’s new dplyr package for R. It creates a relatively small number of verbs to quickly and easily manipulate data. It is generally as fast as data.table but unless you’re already very familiar with data.table the syntax is much easier. There are a number of great introductions and tutorials, which…