Statistical hypothesis testing in wavelet analysis: theoretical developments and applications to Indian rainfall

Schulte, Justin A.

doi:https://doi.org/10.5194/npg-26-91-2019

Articles | Volume 26, issue 2

https://doi.org/10.5194/npg-26-91-2019

© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/npg-26-91-2019

© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 26, issue 2

Research article

|

14 Jun 2019

Research article |

| 14 Jun 2019

Statistical hypothesis testing in wavelet analysis: theoretical developments and applications to Indian rainfall

Justin A. Schulte

Download

Final revised paper (published on 14 Jun 2019)
Supplement to the final revised paper
Preprint (discussion started on 13 Dec 2018)

Interactive discussion

Status: closed

AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment

- Printer-friendly version

- Supplement

RC1: 'Interactive comments on “Statistical Hypothesis Testing in Wavelet Analysis: Theoretical Developments and Applications to India Rainfall”', Anonymous Referee #1, 02 Feb 2019
- AC2: 'Response to Reviewer 1', Justin Schulte, 27 Mar 2019
RC2: '"Statistical Hypothesis Testing in Wavelet Analysis: Theoretical Developments and Applications to India Rainfall” by Justin A. Schulte et al.', Anonymous Referee #2, 18 Mar 2019
- AC1: 'Response to Reviewer 2', Justin Schulte, 27 Mar 2019

Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision

AR by Justin Schulte on behalf of the Authors (27 Mar 2019) Author's response Manuscript

ED: Referee Nomination & Report Request started (04 Apr 2019) by Norbert Marwan

RR by Anonymous Referee #1 (16 Apr 2019)

RR by Anonymous Referee #2 (29 Apr 2019)

ED: Publish subject to minor revisions (review by editor) (30 Apr 2019) by Norbert Marwan

AR by Justin Schulte on behalf of the Authors (01 May 2019) Author's response Manuscript

ED: Publish as is (02 May 2019) by Norbert Marwan

AR by Justin Schulte on behalf of the Authors (02 May 2019)

Short summary

Statistical hypothesis tests in wavelet analysis are used to asses the likelihood that time series features are noise. The choice of test will determine which features emerge as a signal. Tests based on area do poorly at distinguishing abrupt fluctuations from periodic behavior, unlike tests based on arclength that do better. The application of the tests suggests that there are features in Indian rainfall time series that emerge from background noise.