Regime Shift Detection Project
This site tracks the development of the software for regime shift detection in time series known as STARS (Sequential T-test Analysis of Regime Shifts) or SRSD (Sequential Regime Shift Detection) method. The former acronym was used for earlier versions of the software that primarily dealt with shifts in mean. After the package was expanded to include shifts in the variance and correlation, which use the F-test, rather than t-test, the latter acronym became more appropriate.
The SRSD software has been used in a wide variety of applications, ranging from oceanography to climate research to economics (see Overview and references in Google Scholar). It has a number of advantages over other existing methods:
Automatically detects regime shifts (or change points) in mean, variance, and correlation coefficient;
Better performance at the end of time series, indicating a possibility of a shift in real time;
Can be tuned up to detect shifts on different time scales;
No need to calculate anomalies prior to applying the method;
No a priori information about shifts in the series is required;
It can handle time series with autocorrelation, thus separating regimes due to persistence from the true regimes with different statistics.