A Note on Nonnegative DoIt Approximation

REFERENCES

• Bliznyuk , N. , Ruppert , D. , Shoemaker , C. , Regis , R. , Wild , S. and Mugunthan , P. 2008 . “Bayesian Calibration and Uncertainty Analysis for Computationally Expensive Models Using Optimization and Radial Basis Function Approximation,” . Journal of Computational and Graphical Statistics , 17 : 270 – 294 .
   Web of Science ®Google Scholar
• Fielding , M. , Nott , D. J. and Liong , S.-Y. 2011 . “Efficient MCMC Schemes for Computationally Expensive Posterior Distributions,” . Technometrics , 53 : 16 – 28 .
   Web of Science ®Google Scholar
• Joseph , V. R. 2012 . “Bayesian Computation Using Design of Experiments-Based Interpolation Technique” (with discussion), . Technometrics , 54 : 209 – 242 .
   Web of Science ®Google Scholar
• Rasmussen , C. E. 2003 . “Gaussian Processes to Speed Up Hybrid Monte Carlo for Expensive Bayesian Integrals,” . In Bayesian Statistics 7 , Edited by: Bernardo , J. M. , Bayarri , M. J. , Berger , J. O. , Dawid , A. P. , Heckerman , D. , Smith , A. F. M. and West , M. 651 – 659 . New York : Oxford University Press .
   Google Scholar
• Steinberg , D. M. and Jones , B. 2012 . “Comment: DoIt-Some Thoughts on How to Do It,” . Technometrics , 54 : 236 – 238 .
   Web of Science ®Google Scholar
• Ypma , J. 2011 . nloptr: R Interface to NLopt , R Package Version 0.8.9, Vienna, Austria: The R Foundation for Statistical Computing
   Google Scholar