PROFILPELAJAR.COM

Hampel test

The Hampel test (also known as the Hampel identifier or the Hampel method) is a statistical technique that identifies outliers in datasets.[1]

It works by selecting a window of neighbouring points around each point. The median and median absolute deviation (MAD) of these points is calculated, and it is checked whether the central point deviates from the median by more than a certain threshold (the threshold is determined in terms of the MAD).[2] If the point is beyond the limit, it is considered an outlier and is replaced by the median of the selected window.

It is considered a robust model, as it relies on the usage of the median and the MAD, rather than the mean and the standard deviation, which makes it less sensitive to other existing outliers in a window of points. The Hampel filter is a screen used in signal processing that uses the Hampel identifier to replace outlier values with the window median.[3]

References

  1. ^ Roos-Hoefgeest Toribio, Mario; Garnung Menéndez, Alejandro; Roos-Hoefgeest Toribio, Sara; Álvarez García, Ignacio (2025-05-25). "A Novel Approach to Speed Up Hampel Filter for Outlier Detection". Sensors. 25 (11): 3319. doi:10.3390/s25113319. ISSN 1424-8220. PMC 12157161. PMID 40968853.
  2. ^ Lewinson, Eryk (2019-09-26). "Outlier Detection with Hampel Filter". Towards Data Science. Retrieved 2025-10-21.
  3. ^ "The Hampel identifier: Robust outlier detection in a time series". The DO Loop. 2021-06-01. Retrieved 2025-10-21.
Stub icon

This statistics-related article is a stub. You can help Wikipedia by adding missing information.

Content Disclaimer

Informasi ini disarikan dari Wikipedia dan disajikan kembali untuk tujuan edukasi. Konten tersedia di bawah lisensi CC BY-SA 3.0. Kami tidak bertanggung jawab atas ketidakakuratan data yang bersumber dari kontribusi publik tersebut.

  1. The information displayed on this website is sourced in part or in whole from Wikipedia and has been adapted for the purpose of restating it. We strive to provide accurate and relevant information, however:
  2. There is no guarantee of absolute accuracy. Wikipedia is an open, collaborative project that can be edited by anyone, so information is subject to change.
  3. It is not intended to constitute professional advice. The content displayed is for informational and educational purposes only. For important decisions (e.g., medical, legal, or financial), please consult a professional.
  4. Content copyright. Wikipedia is licensed under the Creative Commons Attribution-ShareAlike License (CC BY-SA). This means that content may be reused with appropriate attribution and shared under a similar license.
  5. Responsible use. Any risk arising from the use of information from this website is entirely the responsibility of the user.