It is common decision analysis practice to elicit quantiles of continuous uncertainties and then fit a continuous probability distribution to the corresponding probability-quantile pairs. This process is inconvenient because it requires curve-fitting and the best-fit distribution will often not honor the assessed points. By strategically extending the Johnson Distribution System, we develop a n...

Recent advances in computation technology for simulation/uncertainty analyses have shed new light on the triangular distribution and its use to describe the uncertainty of bounded input phenomena. Herein, we develop a novel fitting procedure for a continuous unimodal (four-parameter) family of distributions on a bounded domain, utilizing three properly selected quantile estimates and an estimat...