DataCafé

Changepoint Detection: Secret Weapon of the Data Scientist

DataCafé Season 1 Episode 5

How can we spot a change in a jet engine vibration that might mean it’s about to fail catastrophically? How can a service forecast adapt to unexpected changes brought about by a pandemic? How might we spot an increase in rate of change of pollution in the atmosphere? The answer to all these questions is changepoints, or rather changepoint detection

Common to all these systems is a set of ordered data, usually a time series of observations or measurements that may be noisy but have some underlying pattern. As the world changes, so those changes might lead to dramatic changes in the measurements and a disruption of the usual pattern. Unless these forecasts or failure-detection systems are updated quickly to take account of a change in measurement data, they will likely produce erroneous or unpredictable results. 

Changepoints have many important applications in areas such as:

  • Climatology
  • Genetic sequencing
  • Finance
  • Medical imaging
  • Forecasting in industry

We speak to statistician Dr. Rebecca Killick from Lancaster University about her work in changepoint detection and how it is a critical part of the statistical toolkit for analysing time series and other ordered data sets. In particular:

  • In forecasting where most methods tend to work on the basis of extrapolating trends, it is essential to know if a changepoint has occurred so that a refreshed model calculation can be started.
  • If there is a change in the underlying dynamics of a system that causes a complex change in the observed output then this can often be detected with a changepoint. This might be indicative of a mechanical failure or impending change in operation or an unobserved event buried deep in a difficult-to-measure environment, like a nuclear reactor. 

With interview guest Dr. Rebecca Killick, Associate Professor of Statistics at Lancaster University.

Further reading

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Recording date: 10 June 2020
Interview date: 5 June 2020

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