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G. Marchuk (1995)
Adjoint Equations and Analysis of Complex Systems
R. Errico (1997)
What is an adjoint modelBulletin of the American Meteorological Society, 78
G. Marchuk, V. Agoshkov, V. Shutyaev (1996)
Adjoint Equations and Perturbation Algorithms in Nonlinear Problems
Harry Markowitz (1971)
Portfolio Selection
P. Lancaster, M. Tismenetsky (1969)
The theory of matrices
N. Bailey, J. Duppenthaler (1980)
Sensitivity analysis in the modelling of infectious disease dynamicsJournal of Mathematical Biology, 10
S. Wallace (2000)
Decision Making Under Uncertainty: Is Sensitivity Analysis of Any Use?Oper. Res., 48
Boca Raton, D. Cacuci (2003)
SENSITIVITY and UNCERTAINTY ANALYSIS
Andrea Saltelli (1999)
Sensitivity analysis: Could better methods be used?Journal of Geophysical Research, 104
(2000)
Sensitivity Analysis, Wiley Series in Probability and Statistics
S. Hora (1997)
Sensitivity, uncertainty, and decision analyses in the prioritization of researchJournal of Statistical Computation and Simulation, 57
J. Wilkinson (1966)
The algebraic eigenvalue problem
Andrea Saltelli, Ratto Marco, A. Terry, Campolongo Francesca, Cariboni Jessica, G. Debora, Saisana Michaela, Tarantola Stefano (2008)
Global Sensitivity Analysis: The Primer
D. Cacuci (1981)
Sensitivity theory for nonlinear systems. II. Extensions to additional classes of responsesJournal of Mathematical Physics, 22
A. Barkley, H. Peterson (2008)
Wheat Variety Selection: An Application of Portfolio Theory to Improve Returns
(1986)
Optimize your farm. ii. lp for whole-farm modeling
(2008)
A Derivation of Forward and Adjoint Sensitivities for ODEs and DAEs
A. Barkley, R. Bowden, J. Shroyer (2006)
KANSAS WHEAT VARIETY SELECTION: COMBINING ECONOMICS AND AGRONOMY TO MAXIMIZE PROFITS AND MINIMIZE RISK
P. Frank, M. Eslami (1980)
Introduction to System Sensitivity TheoryIEEE Transactions on Systems, Man, and Cybernetics, 10
Andrea Saltelli, S. Tarantola, F. Campolongo, M. Ratto (2004)
Sensitivity Analysis in Practice: A Guide to Assessing Scientific Models
A. Lindberg (2003)
Bovine viral Diarrhoea virus infections and its control. A reviewVeterinary Quarterly, 25
D. Cacuci, C. Weber, E. Oblow, J. Marable (1980)
Sensitivity Theory for General Systems of Nonlinear EquationsNuclear Science and Engineering, 75
J. Martins, P. Sturdza, J. Alonso (2003)
The complex-step derivative approximationACM Trans. Math. Softw., 29
L. Garrett (1994)
The Coming Plague: Newly Emerging Diseases in a World Out of Balance
A. Levy (2001)
Solution Sensitivity from General PrinciplesSIAM J. Control. Optim., 40
G. Marchuk, V. Agoshkov (1988)
Conjugate operators and algorithms of perturbation in nonlinear problems I. Principles of construction of conjugate operators, 3
D. Cacuci, M. Ionescu-Bujor, Ionel Navon (2005)
Sensitivity and Uncertainty Analysis, Volume II: Applications to Large-Scale Systems
(1986)
Mathematical Biology I: An Introduction
D. Cacuci (1981)
Sensitivity theory for nonlinear systems. I. Nonlinear functional analysis approachJournal of Mathematical Physics, 22
G. Golub (1983)
Matrix computations
R. Vanderbei (1998)
Linear Programming: Foundations and ExtensionsJournal of the Operational Research Society, 49
[All mathematical models are approximate and their usefulness depends on our understanding the uncertainty inherent in the predictions. Uncertainties can affect the reliability of the results at every stage of computation; they may grow or even shrink as the solution of the model evolves. Often these inherent uncertainties cannot be made arbitrarily small by a more complex model or additional computation and we must understand how the uncertainty in the model parameters, the initial conditions, and the model itself, lead to uncertainties in the model predictions. This chapter is an introductory survey of sensitivity analysis and illustrates how to define the derivative of the model solution as a function of the model input and determine the relative importance of the model parameters on the model predictions.]
Published: Jan 1, 2009
Keywords: Linear Programming Problem; Sensitivity Index; Singular Vector; Initial Value Problem; Algorithmic Differentiation
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