Discussion of ‘Detecting possibly frequent change-points: Wild Binary Segmentation 2 and steepest-drop model selection’
2020 ◽
Vol 49
(4)
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pp. 1076-1080
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AbstractWe congratulate the author for this interesting paper which introduces a novel method for the data segmentation problem that works well in a classical change point setting as well as in a frequent jump situation. Most notably, the paper introduces a new model selection step based on finding the ‘steepest drop to low levels’ (SDLL). Since the new model selection requires a complete (or at least relatively deep) solution path ordering the change point candidates according to some measure of importance, a new recursive variant of the Wild Binary Segmentation (Fryzlewicz in Ann Stat 42:2243–2281, 2014, WBS) named WBS2, has been proposed for candidate generation.
2020 ◽
Vol 49
(4)
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pp. 1099-1105
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2020 ◽
Vol 49
(4)
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pp. 1027-1070
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2020 ◽
Vol 49
(4)
◽
pp. 1096-1098
2020 ◽
Vol 49
(4)
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pp. 1090-1095
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2020 ◽
Vol 49
(4)
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pp. 1071-1075
2010 ◽
Vol 19
(17)
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pp. 3603-3619
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