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Detecting multiple local extrema via wild binary segmentation

Where:  TU Delft, Faculty EWI, Mekelweg 4, Room D@ta.
When:  6th of June 2017 tot 5th of June 2017
Starttime  12:45

On Tuesday (06/06/2017), we have another interesting talk in our Probability and Statistics seminar series at TU Delft. All of you are very welcome.

 

Yining Chen (LSE)

When: Tuesday June 6th, 12:45
Where: TU Delft, Faculty EWI, Mekelweg 4, Room D@ta.

 

Detecting multiple local extrema via wild binary segmentation

We consider the univariate nonparametric regression problem, where given n observations, the goal is to detect the number and locations of multiple local maxima and minima in the curve. We propose a new approach that combines the ideas of wild binary segmentation (Fryzlewicz, 2014) and mode estimation using isotone regression. We show that our procedure consistently estimates the number of local extrema, and is minimax optimal (up to a logarithmic factor) in estimating the locations of these points. Moreover, we show that the computational complexity of our method is near-optimal (i.e., up to a logarithmic factor, of order n). Finally, we discuss how our approach could be extended to detect other interesting features, such as inflection points.


More details here: http://goo.gl/TXD1Sw

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YEQT workshop

Eurandom
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7th Stochastic Modelling meeting (StochMod 2018)

13th of June 2018 - 15th of June 2018 Read more...

ACM SIGMETRICS FOR 2018

Irvine, California, USA
18th of June 2018 - 22nd of June 2018 Read more...


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