Multiple change point estimation based on moving sum statistics

Add to your list(s) Download to your calendar using vCal

• Claudia Kirch (Magdeburg)
• Friday 11 May 2018, 16:00-17:00
• MR12.

If you have a question about this talk, please contact Quentin Berthet.

Using the example of changes in the mean we introduce change point estimators for multiple changes based on moving sum statistics. For a given bandwidth we prove consistency of these estimators as well as their asymptotic limit distribution. In many practical situations a single bandwidth is not sufficient to detect all change points, but instead several bandwidths need to be used. We discuss extensions based on information criteria to combine this multiscale information in a consistent way. Finally, extensions to a very general setting based on estimating functions are discussed. These extensions allow for more robust methods in the mean change situation as well as for more complex change point problems such as changes in the time series structure.

This talk is part of the Statistics series.

This talk is included in these lists:

• All CMS events
• All Talks (aka the CURE list)
• CMS Events
• Cambridge Forum of Science and Humanities
• Cambridge Language Sciences
• Cambridge talks
• Chris Davis' list
• DPMMS Lists
• DPMMS info aggregator
• DPMMS lists
• Guy Emerson's list
• Hanchen DaDaDash
• Interested Talks
• MR12
• Machine Learning
• School of Physical Sciences
• Statistical Laboratory info aggregator
• Statistics
• Statistics Group
• bld31
• custom
• rp587

Note that ex-directory lists are not shown.