Estimating the standard deviation of soil properties with limited samples through the Bayesian approach

J. P. Wang, Yun Xu

Research output: Contribution to journalArticlepeer-review

9 Scopus citations

Abstract

Characterizing the standard deviation of soil properties is important to a geotechnical probabilistic analysis, and the task is usually achieved with sufficient samples. However, sometimes soil samples or soil tests in a project could be limited (e.g., only one sample), making classical statistics approaches less applicable to the estimating. In this technical note, we introduce a new Bayesian algorithm to estimate the standard deviation of soil properties, using limited project-specific samples along with relevant prior information from the literature. In addition to the methodology, a few demonstrations are also given in the paper, to re-evaluate the standard deviation of soil properties with the new algorithm. Like many Bayesian algorithms, the new application could be useful for site characterizations when samples are limited.

Original languageEnglish
Pages (from-to)271-278
Number of pages8
JournalBulletin of Engineering Geology and the Environment
Volume74
Issue number1
DOIs
StatePublished - 1 Jan 2015

Keywords

  • Limited samples
  • Soil properties
  • Standard deviation
  • The Bayesian approach

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