Anomaly detection by using R

8/2017 UPDATE:  My ML based anomales and patterns change detection tool - SETDS was redeveloped on R. See more details:

Igor = I go R. I have redeveloped SETDS on R = SonR

_______________________________________ original post:
I have already suggested (and partially tested) to use R to developed an exception (anomaly) detector by applying my SETDS Methodology. You can find some simple examples in my CMG.org papers or here or at the following post:

SEDS-Lite: Using Open Source Tools (R, BIRT, MySQL) to Report and Analyze Performance Data 

I did not used any specific statistical packages for that 
(e.g.  qcc), but I see now some very specific ones have been appearing that could be used to detect different type of anomalies. 

Here is one at  Twitter Blogs:
Introducing practical and robust anomaly detection in a time series

Not sure how the approach evaluate (score) significance of the anomaly like EV meta-metric does in my SETDS Methodology. I see at least it puts them in some categories such as "global anomalies" and "local anomalies".

 I may want to test the package. You?