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A test for local white noise (and the absence of aliasing) in locally stationary wavelet time series

By Guy Nason

Appears in collection : Thematic month on statistics - Week 3: Processus / Mois thématique sur les statistiques - Semaine 3 : Processus

This talk develops a new test for local white noise which also doubles as a test for the lack of aliasing in a locally stationary wavelet process. We compare and contrast our new test with the aliasing test for stationary time series due to Hinich and co-authors. We show that the test is robust to mismatch of analysis and synthesis wavelet. We demonstrate the effectiveness of the test on some simulated examples and on an example from wind energy.

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Citation data

  • DOI 10.24350/CIRM.V.18932103
  • Cite this video Nason, Guy (18/02/2016). A test for local white noise (and the absence of aliasing) in locally stationary wavelet time series. CIRM. Audiovisual resource. DOI: 10.24350/CIRM.V.18932103
  • URL https://dx.doi.org/10.24350/CIRM.V.18932103

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