The prediction of model outcomes frequently hinges on understanding the variability introduced by input parameters to the model. Such parametric influences can encode stochastic fluctuations, model-form error, and geometric uncertainty. Therefore, developing robust techniques for predicting the uncertainty resulting from this parametric variatio...
Creator:
Narayan, Akil (University of Massachusetts Dartmouth)
Created:
2015-06-18
Contributed By:
University of Minnesota, Institute for Mathematics and its Applications.
The prediction of model outcomes frequently hinges on understanding the variability introduced by input parameters to the model. Such parametric influences can encode stochastic fluctuations, model-form error, and geometric uncertainty. Therefore, developing robust techniques for predicting the uncertainty resulting from this parametric variatio...
Creator:
Narayan, Akil (University of Massachusetts Dartmouth)
Created:
2015-06-19
Contributed By:
University of Minnesota, Institute for Mathematics and its Applications.
