Multiscale Change Point Inference
Seminar Room 1, Newton Institute
AbstractStatistical 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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