Bayesian statistics is an approach to data analysis based on Bayes' theorem, where
available knowledge about parameters in a statistical model is updated with the information …

17 Decision-Making Options for Managing Risk Page 1 SPM 2539 17 Decision-Making
Options for Managing Risk Coordinating Lead Authors: Mark New (South Africa), Diana …

While the majority of companies anticipated the negative and severe impacts of the COVID-
19 pandemic on the supply chains (SC), most of them lacked guidance on how to model …

Prior Knowledge Elicitation: The Past, Present, and Future Page 1 Bayesian Analysis (2024)
19, Number 4, pp. 1129–1161 Prior Knowledge Elicitation: The Past, Present, and Future ∗ …

" Since the publication of the first edition, Bayesian statistics is, arguably, still not the norm in
the formal quantitative methods training of social scientists. Typically, the only introduction …

Expert elicitation is deployed when data are absent or uninformative and critical decisions
must be made. In designing an expert elicitation, most practitioners seek to achieve best …

In recent years, governments are increasingly interested in developing public–private
partnerships such as outsourcing logistics to service providers to benefit from better …

The goal of this paper is to review and critically discuss the philosophical aspects of
probabilistic seismic hazard analysis (PSHA). Given that estimates of seismic hazard are …

At the outset of an analysis, there is a need to interact with the problem-owners to
understand their perspectives on the issues. This understanding leads to the construction of …

This study focuses on measuring the influence of critical Human and Organizational Factors
(HOFs) on human error occurrence in structural design and construction tasks within the …