Forest plots are most commonly used in reporting meta-analyses, but can be profitably used to summarise the results of a fitted model. They essentially display the estimates for model parameters and their corresponding confidence intervals. Matt Shotwell just posted a message to the R-help mailing list with his lattice-based solution to the problem of creating forest plots in R. I 
![ABC lectures [finale]](http://www.r-bloggers.com/wp-content/uploads/2010/10/freed-e1288537702984.jpg?w=345&h=482)
The latest version of my ABC slides is on slideshare. To conclude with a pun, I took advantage of the newspaper clipping generator once pointed out by Andrew. (Note that nothing written in the above should be taken seriously.) On the serious side, I managed to cover most of the 300 slides (!) over the 
I decided to go use ggplot2 more frequently and go through everything. For future reference I will start a series of blog posts on ggplot2. Scatter plot: In my next post, I will change the axis labels.
Last time I talked about adapting graphs for presentations. This time I’m putting some of the concepts I discussed there into action, with a presentation of Immer’s barley dataset. This is a classic dataset, originally published in 1934; in 1993 Bill Cleveland mentioned it in his book Visualising Data on account of how it may 
I’m in the process of buying a used car. Since I enjoy making these decisions as complicated as possible, I’ve written some R code to scrape relevant websites for informative data. I’ve written this up as a blog entry because I think it’s a decent example of how one might use the XML...
In the debate over the accuracy of the global temperature nothing is more evident than errors in the location data for stations in the GHCN inventory. That inventory is the primary source for all the temperature series. One question is “do these mistakes make a difference?” If one believes as I do that the record 
regor Gorjanc published an interesting article “Using Sweave with LyX” in R News in 2008, which (I believe) makes it much easier to use Sweave. I use command-line tools a lot every day, but I am still “GUI-addicted”. (I don’t want to comment more about Microsoft Word here.) LyX is a somewhat WYSIWYG tool based
I am currently working on rectifying the GHCN station list to improve the location information. Its the kind of database work that is mind numbingly tedious and a PITA in R. not because R lacks capabilities, its just tough and not very sexy to matching and fuzzy matching and greping and blah blah blah. Instead, 
…was the tongue-in-cheek title of an image that I posted to Twitpic this week. It shows the usage of the word “novel” in PubMed article titles over time. As someone correctly pointed out at FriendFeed, it needs to be corrected for total publications per year. It was inspired by a couple of items that caught 
par (mar=c(3,3,2,1), mgp=c(2,.7,0), tck=-.01) Thank you....
Zero Inflated Models and Generalized Linear Mixed Models with R.
Zuur, Saveliev, Ieno (2012).
