Oberkampf,
W.
, and
Roy,
C.
, 2010, Verification and Validation in Scientific Computing,
Cambridge University Press,
New York.

Hu,
K.
, 2013, “
2014 V&V Challenge: Problem Statement,” Sandia National Laboratories, Albuquerque, NM and Livermore, CA, Technical Report No. SAND2013-10486P.

Adams,
B. M.
,
Bauman,
L. E.
,
Bohnhoff,
W. J.
,
Dalbey,
K. R.
,
Eddy,
J. P.
,
Ebeida,
M. S.
,
Eldred,
M. S.
,
Hough,
P. D.
,
Hu,
K. T.
,
Jakeman,
J. D.
,
Swiler,
L. P.
,
Stephens,
J. A.
,
Vigil,
D. M.
, and
Wildey,
T. M.
, 2014, “
Dakota, a Multilevel Parallel Object-Oriented Framework for Design Optimization, Parameter Estimation, Uncertainty Quantification, and Sensitivity Analysis: Version 6.1 Users Manual,” Sandia National Laboratories, Albuquerque, NM, Technical Report No. SAND2014-4633.

Adams,
B.
,
Ebeida,
M.
,
Eldred,
M.
,
Jakeman,
J.
,
Swiler,
L.
,
Bohnhoff,
W.
,
Dalbey,
K.
,
Eddy,
J.
,
Hu,
K.
,
Vigil,
D.
,
Bauman,
L.
, and
Hough,
P.
, 2011, “
Dakota, a Multilevel Parallel Object-Oriented Framework for Design Optimization, Parameter Estimation, Uncertainty Quantification, and Sensitivity Analysis,” Sandia National Laboratories, Albuquerque, NM and Livermore, CA, Technical Report No. SAND2011-9106.

Oberkampf,
W.
,
Pilch,
M.
, and
Trucano,
T.
, 2007, “
Predictive Capability Maturity Model for Computational Modeling and Simulation,” Sandia National Laboratories, Albuquerque, NM and Livermore, CA, Technical Report No. SAND2007-5948.

Montgomery,
D.
, and
Runger,
G.
, 1994, Applied Statistics and Probability for Engineers,
Wiley,
New York.

Hahn,
G.
, and
Meeker,
W.
, 1991, Statistical Intervals—A Guide for Practitioners,
Wiley,
New York.

Computer Software by Minitab, Inc., “
Minitab 17 Statistical Software,”

www.minitab.com
Howe,
W.
, 1969, “
Two-Sided Tolerance Limits for Normal Populations—Some Improvements,” J. Am. Stat. Assoc.,
64(326), pp. 610–620.

Romero,
V.
,
Swiler,
L.
,
Urbina,
A.
, and
Mullins,
J.
, 2013, “
A Comparison of Methods for Representing Sparsely Sampled Random Quantities,” Sandia National Laboratories, Albuquerque, NM and Livermore, CA, Technical Report No. SAND2013-4561.

Iman,
R. L.
, and
Shortencarier,
M. J.
, 1984, “
A Fortran 77 Program and User's Guide for the Generation of Latin Hypercube Samples for Use With Computer Models,” Sandia National Laboratories, Albuquerque, NM, Technical Report No. NUREG/CR-3624, SAND83-2365.

Saltelli,
A.
,
Tarantola,
S.
,
Compolongo,
F.
, and
Ratto,
M.
, 2004, Sensitivity Analysis in Practice: A Guide to Assessing Scientific Models,
Wiley,
New York.

Dennis,
J. E.
,
Gay,
D. M.
, and
Welsch,
R. E.
, 1981, “
ALGORITHM 573: NL2SOL—An Adaptive Nonlinear Least-Squares Algorithm,” ACM Trans. Math. Software,
7(3), pp. 369–383.

[CrossRef]
Xiu,
D.
, 2010, Numerical Methods for Stochastic Computations: A Spectral Method Approach,
Princeton University Press,
Princeton, NJ.

Hastie,
T.
,
Tibshirani,
R.
, and
Friedman,
J.
, 2001, The Elements of Statistical Learning: Data Mining, Inference, and Prediction: With 200 Full-Color Illustrations,
Springer-Verlag,
Berlin.

Bichon,
B.
,
Eldred,
M.
,
Swiler,
L.
,
Mahadevan,
S.
, and
McFarland,
J.
, 2008, “
Efficient Global Reliability Analysis for Nonlinear Implicit Performance Functions,” AIAA J.,
46(10), pp. 2459–2468.

[CrossRef]
MacKay,
D.
, 1998, “
Introduction to Gaussian Processes,” Neural Networks and Machine Learning, Vol.
168,
C. M. Bishop
, ed., Springer, Berlin, pp. 133–165.