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Being Sensitive to Uncertainty
March/April 2007 (vol. 9 no. 2)
pp. 10-20
ASCII Text
x 
 
Leon M. Arriola, James M. Hyman, "Being Sensitive to Uncertainty," Computing in Science and Engineering, vol. 9, no. 2, pp. 10-20, March/April, 2007.
 
 
BibTex
x
 
@article{ 10.1109/MCSE.2007.27,
author = {Leon M. Arriola and James M. Hyman},
title = {Being Sensitive to Uncertainty},
journal ={Computing in Science and Engineering},
volume = {9},
number = {2},
issn = {1521-9615},
year = {2007},
pages = {10-20},
doi = {http://doi.ieeecomputersociety.org/10.1109/MCSE.2007.27},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - MGZN
JO - Computing in Science and Engineering
TI - Being Sensitive to Uncertainty
IS - 2
SN - 1521-9615
SP10
EP20
EPD - 10-20
A1 - Leon M. Arriola,
A1 - James M. Hyman,
PY - 2007
KW - stochastic
KW - sensitivity
KW - uncertainty
KW - analysis
KW - volatility
VL - 9
JA - Computing in Science and Engineering
ER -
 
Leon M. Arriola, University of Wisconsin?Whitewater
James M. Hyman, Los Alamos National Laboratory
Predictive modeling's effectiveness is hindered by inherent uncertainties in the input parameters. Sensitivity and uncertainty analysis quantify these uncertainties and identify the relationships between input and output variations, leading to the construction of a more accurate model. This survey introduces the application, implementation, and underlying principles of sensitivity and uncertainty quantification.
Index Terms:
stochastic, sensitivity, uncertainty, analysis, volatility
Citation:
Leon M. Arriola, James M. Hyman, "Being Sensitive to Uncertainty," Computing in Science and Engineering, vol. 9, no. 2, pp. 10-20, March-April 2007, doi:10.1109/MCSE.2007.27
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