## » Multi-Group comparison in Partial Least Squares Path Models • May 28, 11:22 AM

This post is about multi-group partial least squares path modeling (PLS-PM).

## » Yet another gray theme for R base graphics • Jul 25, 11:04 AM

Among things I like with R is that if you are not happy with default settings, e.g. for graphics, then you can usually update some parameters or make your own plotting function.

## » Writing a book • Jul 22, 09:24 PM

I spent the last month working hard to finish my book on biomedical statistics using R.

## » R, pipes and Co. • Apr 30, 12:11 PM

The R language is rapidly changing. I am afraid I'm still teaching R like I learned and liked it 10 years ago (but I was already aware of replicate() long ago :-) although I try to keep regularly informed of what's new on CRAN.

## » R Graphs Cookbook • Jan 15, 02:50 PM

I just finished reading the R Graphs Cookbook* (2nd ed.), by Jaynal Abedin and Hrishi V. Mittal, edited by Packt Publishing.

## » Emacs Org-mode and literate programming • Aug 6, 08:37 PM

I've been using Emacs for editing and evaluating R code with ESS for a long time now. I also like Emacs for editing statistical reports and compiling them using knitr (and before that, Sweave), using plain LaTeX or just RMarkdown. Now, I'm getting interested in org-mode as an alternative to noweb, which I previously used when looking for a way to integrate different programming languages (e.g., sh, sed, and R) into the same document.

## » user2014 • Jul 4, 09:21 AM

Here are some notes on user2014 (no it's not one of the anonymous poster on Stack Exchange!). The GitHub homepage can be found at https://github.com/user2014.

## » Reproducible research with R • Apr 19, 11:03 AM

I just finished reading two recent books in the R Series from Chapman & Hall: Reproducible research with R and RStudio (Christopher Gandrud), and Dynamic documents with R and knitr (Yihui Xie).

## » Audit trails in statistical project • Mar 1, 08:03 PM

In the context of a statistical project, sanity checking refers to the verification of raw data: whether they make sense, if there are any coding errors that are apparent from the range of data values, or if some data should be recoded or set as missing (Baum, CF, An introduction to Stata programming,(a) Stata Press, 2009, p. 79).

## » Interactive data visualization with cranvas • Oct 27, 08:35 PM

One of the advantage of R over other popular statistical packages is that it now has "natural" support for interactive and dynamic data visualization. This is, for instance, something that is lacking with the Python ecosystem for scientific computing (Mayavi or Enthought Chaco are just too complex for what I have in mind).