Articles | Volume 16, issue 4/5
https://doi.org/10.5194/se-16-367-2025
https://doi.org/10.5194/se-16-367-2025
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: 1,560 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
1,042 298 220 1,560 35 69
  • HTML: 1,042
  • PDF: 298
  • XML: 220
  • Total: 1,560
  • BibTeX: 35
  • EndNote: 69
Views and downloads (calculated since 30 Sep 2024)
Cumulative views and downloads (calculated since 30 Sep 2024)

Viewed (geographical distribution)

Total article views: 1,560 (including HTML, PDF, and XML) Thereof 1,518 with geography defined and 42 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 06 Dec 2025
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.
Share