Solid Earth
Solid Earth
SE
Articles | Volume 16, issue 4/5
Articles | Volume 16, issue 4/5
https://doi.org/10.5194/se-16-367-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/se-16-367-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 16, issue 4/5
Research article
 | 
15 May 2025
Research article |  | 15 May 2025

Unbiased statistical length analysis of linear features: adapting survival analysis to geological applications

Gabriele Benedetti, Stefano Casiraghi, Daniela Bertacchi, and Andrea Bistacchi

Viewed

Total article views: 2,819 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
2,153 405 261 2,819 50 88
  • HTML: 2,153
  • PDF: 405
  • XML: 261
  • Total: 2,819
  • BibTeX: 50
  • EndNote: 88
Views and downloads (calculated since 30 Sep 2024)
Cumulative views and downloads (calculated since 30 Sep 2024)

Viewed (geographical distribution)

Total article views: 2,819 (including HTML, PDF, and XML) Thereof 2,579 with geography defined and 240 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 11 Apr 2026
Download
Short summary
At any scale, the limited size of a study area introduces a bias in the interpretation of linear features, defined as right-censoring bias. We show the effects of not considering such bias and apply survival analysis techniques to obtain unbiased estimates of multiple parametrical distributions in three censored length datasets. Finally, we propose a novel approach to select the most representative model from a sensible candidate pool using the probability integral transform technique.
Read more
Share