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Multiscale Change Point Inference

Date: 
Tuesday 14th January 2014 - 11:30 to 12:15
Venue: 
INI Seminar Room 1
Abstract: 
Statistical MUltiscale Change point Estimation (SMUCE) is an inference tool for estimation and confidence statements about a change-point function and its main characteristics location, size and number of jumps. SMUCE detects these features on all scales in an optimal fashion. Fast computation of SMUCE via dynamic programming is addressed and data from ion channel recordings, photo emission spectroscopy and CGH array analysis will be analyzed.
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University of Cambridge Research Councils UK
    Clay Mathematics Institute London Mathematical Society NM Rothschild and Sons