Forthcoming Issue

The following papers are expected to appear in
Volume 28, Number 2, April 2018

Computer Experiments and Uncertainty Quantification

1. SS-2016-0217
doi:10.5705/ss.202016.0217
Computer experiments: prediction accuracy, sample size and model complexity revisited
Or Harari, Derek Bingham, Angela Dean and Dave Higdon
2. SS-2016-0130
doi:10.5705/ss.202016.0130
Sensitivity analysis and emulation for functional data using bayesian adaptive splines
Devin Francom, Bruno Sanso, Ana Kupresanin and Gardar Johannesson
3. SS-2016-0035
doi:10.5705/ss.202016.0035
Sensitivity analysis using permutations
Shifeng Xiong, Xu He, Yuanzhen He and Weiyan Mu
4. SS-2016-0165
doi:10.5705/ss.202016.0165
A sequential maximum projection design framework for computer experiments with inert factors
Shan Ba, William R. Myers and Dianpeng Wang
5. SS-2016-0255
doi:10.5705/ss.202016.0255
Single nugget kriging
Minyong R. Lee and Art B. Owen
6. SS-2015-0404
doi:10.5705/ss.202015.0404
Orthogonal Gaussian process models
Matthew Plumlee and V. Roshan Joseph
7. SS-2015-0367
doi:10.5705/ss.202015.0367
Uncertainty quantification with Ł\-stable-process models
Rui Tuo
8. SS-2015-0249
doi:10.5705/ss.202015.0249
Gaussian process modeling with boundary information
Matthias Hwai Yong Tan
9. SS-2015-0344
doi:10.5705/ss.202015.0344
Nonparametric functional calibration of computer models
D. Andrew Brown and Sez Atamturktur
10. SS-2016-0160
doi:10.5705/ss.202016.0160
Sequential design of experiments for estimating quantiles of black-box functions
T. Labopin-Richard and V. Picheny
11. SS-2016-0163
doi:10.5705/ss.202016.0163
Sequential Pareto minimization of physical systems using calibrated computer simulators
Po-Hsu Allen Chen, Thomas J. Santner and Angela M. Dean
12. SS-2016-0138
doi:10.5705/ss.202016.0138
Exploiting variance reduction potential in local Gaussian process search
Chih-Li Sung, Robert B. Gramacy and Benjamin Haaland
13. SS-2016-0403
doi:10.5705/ss.202016.0403
Bayesian calibration of multistate stochastic simulators
Mathew T. Pratola and Oksana Chkrebtii
14. SS-2016-0162
doi:10.5705/ss.202016.0162
Statistical-physical estimation of pollution emission
Youngdeok Hwang, Emre Barut and Kyongmin Yeo
15. SS-2017-0138
doi:10.5705/ss.202017.0138
Surrogate-assisted tuning for computer experiments with qualitative and quantitative parameters
Jiahong K. Chen, Ray-Bing Chen, Akihiro Fujii, Reiji Suda and Weichung Wang
16. SS-2016-0209
doi:10.5705/ss.202016.0209
Prediction based on the Kennedy-O'Hagan calibration model: asymptotic consistency and other properties
Rui Tuo and C. F. Je Wu
17. SS-2016-0151
doi:10.5705/ss.202016.0151
Controlling correlations in sliced Latin hypercube designs
Jiajie Chen and Peter Qian
18. SS-2017-0091
doi:10.5705/ss.202017.0091
Generalized sparse precision matrix selection for fitting multivariate
Sam Davanloo Tajbakhsh, Necdet Serhat Aybat and Enrique del Castillo
   
General  
19. SS-2016-0041
doi:10.5705/ss.202016.0041
High-dimensional Gaussian copula regression: adaptive estimation and statistical inference
T. Tony Cai and Linjun Zhang
20. SS-2016-0434
doi:10.5705/ss.202016.0434
Multi-asset empirical martingale price estimators for financial derivatives
Shih-Feng Huang and Guan-Chih Ciou
21. SS-2016-0080
doi:10.5705/ss.202016.0080
Flexible imension reduction in regression
Tao Wang and Lixing Zhu
22. SS-2016-0441
doi:10.5705/ss.202016.0441
Fully efficient robust estimation, outlier detection and variable selection via penalized regression
Dehan Kong, Howard D. Bondell and Yichao Wu
23. SS-2016-0167
doi:10.5705/ss.202016.0167
Scalable Bayesian variable selection using nonlocal prior densities in ultrahigh-dimensional settings
Minsuk Shin, Anirban Bhattacharya and Valen E. Johnson
24. SS-2016-0378
doi:10.5705/ss.202016.0378
Estimating standard errors for importance sampling estimators with multiple Markov chains
Vivekananda Roy, Aixin Tan and James M. Flegal