content

Statistica Sinica

Volume 28, Number 2, April 2018

corresponding author*
Computer Experiments and Uncertainty Quantification
	Editorial　 Robert Gramcy, Ying Hung and Jeff Wu		551
	Uncertainty quantification with α-stable-process models Rui Tuo*		doi:10.5705/ss.202015.0367 553
	Exploiting variance reduction potential in local Gaussian process search Chih-Li Sung, Robert B. Gramacy and Benjamin Haaland*	Supp	doi:10.5705/ss.202016.0138 577
	Orthogonal Gaussian process models Matthew Plumlee* and V. Roshan Joseph	Supp	doi:10.5705/ss.202015.0404 601
	Gaussian process modeling with boundary information Matthias Hwai Yong Tan*		doi:10.5705/ss.202015.0249 621
	Single nugget Kriging Minyong R. Lee* and Art B. Owen	Supp	doi:10.5705/ss.202016.0255 649
	Sequential Pareto minimization of physical systems using calibrated computer simulators Po-Hsu Allen Chen*, Thomas J. Santner and Angela M. Dean	Supp	doi:10.5705/ss.202016.0163 671
	Bayesian calibration of multistate stochastic simulators Mathew T. Pratola and Oksana Chkrebtii*	Supp	doi:10.5705/ss.202016.0403 693
	Nonparametric functional calibration of computer models D. Andrew Brown* and Sez Atamturktur	Supp	doi:10.5705/ss.202015.0344 721
	Prediction based on the Kennedy-O'Hagan calibration model: asymptotic consistency and other properties Rui Tuo* and C. F. Jeff Wu	Supp	doi:10.5705/ss.202016.0209 743
	Surrogate-assisted tuning for computer experiments with qualitative and quantitative parameters Jiahong K. Chen, Ray-Bing Chen*, Akihiro Fujii, Reiji Suda and Weichung Wang		doi:10.5705/ss.202017.0138 761
	Sensitivity analysis and emulation for functional data using Bayesian adaptive splines Devin Francom*, Bruno Sansó, Ana Kupresanin and Gardar Johannesson	Supp	doi:10.5705/ss.202016.0130 791
	Sensitivity analysis using permutations Shifeng Xiong, Xu He, Yuanzhen He and Weiyan Mu*	Supp	doi:10.5705/ss.202016.0035 817
	Controlling correlations in sliced Latin hypercube designs Jiajie Chen and Peter Qian*	Supp	doi:10.5705/ss.202016.0151 839
	Sequential design of experiments for estimating quantiles of black-box functions T. Labopin-Richard and V. Picheny*	Supp	doi:10.5705/ss.202016.0160 853
	A sequential maximum projection design framework for computer experiments with inert factors Shan Ba, William R. Myers and Dianpeng Wang*		doi:10.5705/ss.202016.0165 879
	Computer experiments: prediction accuracy, sample size and model complexity revisited Ofir Harari*, Derek Bingham, Angela Dean and Dave Higdon	Supp	doi:10.5705/ss.202016.0217 899
	Statistical-physical estimation of pollution emission Youngdeok Hwang, Emre Barut* and Kyongmin Yeo	Supp	doi:10.5705/ss.202016.0162 921
	Generalized sparse precision matrix selection for fitting multivariate Gaussian random fields to large data sets Sam Davanloo Tajbakhsh, Necdet Serhat Aybat and Enrique del Castillo*	Supp	doi:10.5705/ss.202017.0091 941
General
	High-dimensional Gaussian copula regression: adaptive estimation and statistical inference T. Tony Cai and Linjun Zhang*	Supp	doi:10.5705/ss.202016.0041 963
	Multi-asset empirical martingale price estimators for financial derivatives Shih-Feng Huang* and Guan-Chih Ciou	Supp	doi:10.5705/ss.202016.0434 995
	Flexible dimension reduction in regression Tao Wang and Lixing Zhu*		doi:10.5705/ss.202016.0080 1009
	Fully efficient robust estimation, outlier detection and variable selection via penalized regression Dehan Kong, Howard D. Bondell* and Yichao Wu	Supp	doi:10.5705/ss.202016.0441 1031
	Scalable Bayesian variable selection using nonlocal prior densities in ultrahigh-dimensional settings Minsuk Shin, Anirban Bhattacharya* and Valen E. Johnson	Supp	doi:10.5705/ss.202016.0167 1053
	Estimating standard errors for importance sampling estimators with multiple Markov chains Vivekananda Roy, Aixin Tan* and James M. Flegal	Supp	doi:10.5705/ss.202016.0378 1079
	Errata-1		1103
	Errata-2		1105