Breakout detection in R

Oct 29, 2014

Say you have time series data and you want to detect significant changes, but there’s also a lot of noise to sift through. Twitter released an open source R package, BreakoutDetection, to help with that.

Our main motivation behind creating the package has been to develop a technique to detect breakouts which are robust, from a statistical standpoint, in the presence of anomalies. The BreakoutDetection package can be used in wide variety of contexts. For example, detecting breakout in user engagement post an A/B test, detecting behavioral change, or for problems in econometrics, financial engineering, political and social sciences.

Was a quick installation and worked as expected for me. Twitter has released plenty of open source projects, but I think this is the first R package. Nice.

Favorites

Best Data Visualization Projects of 2016

Here are my favorites for the year.

Real Chart Rules to Follow

There are rules—usually for specific chart types meant to be read in a specific way—that you shouldn’t break. When they are, everyone loses. This is that small handful.

Shifting Incomes for American Jobs

For various occupations, the difference between the person who makes the most and the one who makes the least can be significant.

Divorce and Occupation

Some jobs tend towards higher divorce rates. Some towards lower. Salary also probably plays a role.