References

• 2000A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output from a Computer Code8,233 cited
• 2003Latin hypercube sampling and the propagation of uncertainty in analyses of complex systems2,707 cited
• 2010DAKOTA : a multilevel parallel object-oriented framework for design optimization, parameter estimation, uncertainty quantification, and sensitivity analysis. Version 5.0, user's manual.775 cited
• 2014Dakota, a multilevel parallel object-oriented framework for design optimization, parameter estimation, uncertainty quantification, and sensitivity analysis version 6.0 theory manual188 cited
• 2011Likelihood-based representation of epistemic uncertainty due to sparse point data and/or interval data156 cited
• 2012Distribution type uncertainty due to sparse and imprecise data65 cited
• 2008The use of kernel densities and confidence intervals to cope with insufficient data in validation experiments41 cited
• 2013A comparison of methods for representing sparsely sampled random quantities.14 cited
• 2013A Comparison of Methods for Representing and Aggregating Uncertainties Involving Sparsely Sampled Random Variables - More Results10 cited
• 2018Simple Effective Conservative Treatment of Uncertainty From Sparse Samples of Random Variables and Functions9 cited
• 2019Real-Space Model Validation and Predictor-Corrector Extrapolation applied to the Sandia Cantilever Beam End-to-End UQ Problem8 cited
• 2017Evaluation of a Simple UQ Approach to Compensate for Sparse Stress-Strain Curve Data in Solid Mechanics Applications