A Simple Approach to Emulation for Computer Models With Qualitative and Quantitative Factors
暂无分享,去创建一个
[1] David B. Dunson,et al. Gaussian process models , 2013 .
[2] C. F. Jeff Wu,et al. Experiments , 2021, Wiley Series in Probability and Statistics.
[3] Alexander Graham,et al. Kronecker Products and Matrix Calculus: With Applications , 1981 .
[4] Søren Nymand Lophaven,et al. DACE - A Matlab Kriging Toolbox, Version 2.0 , 2002 .
[5] Richard J. Beckman,et al. A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output From a Computer Code , 2000, Technometrics.
[6] J. Sacks,et al. Analysis of protein activity data by Gaussian stochastic process models. , 1999, Journal of biopharmaceutical statistics.
[7] Donald R. Jones,et al. Efficient Global Optimization of Expensive Black-Box Functions , 1998, J. Glob. Optim..
[8] Peter Z. G. Qian,et al. Gaussian Process Models for Computer Experiments With Qualitative and Quantitative Factors , 2008, Technometrics.
[9] A. O'Hagan,et al. Predicting the output from a complex computer code when fast approximations are available , 2000 .
[10] T. J. Mitchell,et al. Bayesian design and analysis of computer experiments: Use of derivatives in surface prediction , 1993 .
[11] Peter Z. G. Qian,et al. Sliced space-filling designs , 2009 .
[12] Thomas J. Santner,et al. Prediction for Computer Experiments Having Quantitative and Qualitative Input Variables , 2009, Technometrics.
[13] Carolyn Conner Seepersad,et al. Building Surrogate Models Based on Detailed and Approximate , 2004, DAC 2004.
[14] T. J. Mitchell,et al. Bayesian Prediction of Deterministic Functions, with Applications to the Design and Analysis of Computer Experiments , 1991 .
[15] Søren Nymand Lophaven,et al. Aspects of the Matlab toolbox DACE , 2002 .
[16] Peter Z. G. Qian,et al. Bayesian Hierarchical Modeling for Integrating Low-Accuracy and High-Accuracy Experiments , 2008, Technometrics.
[17] Dawn Hunter. The most general methodology for creating a valid correlation matrix for risk management and option pricing purposes , 2000 .
[18] William J. Welch,et al. Screening the Input Variables to a Computer Model Via Analysis of Variance and Visualization , 2006 .
[19] Barry L. Nelson,et al. Stochastic kriging for simulation metamodeling , 2008, 2008 Winter Simulation Conference.
[20] Runze Li,et al. Design and Modeling for Computer Experiments , 2005 .
[21] Pritam Ranjan,et al. Gaussian Process Models and Interpolators for Deterministic Computer Simulators , 2010, 1003.1315.
[22] Sonja Kuhnt,et al. Design and analysis of computer experiments , 2010 .
[23] R. Rebonato,et al. The most general methodology for creating a valid correlation matrix for risk management and option pricing purposes , 2000 .
[24] Runze Li,et al. Analysis of Computer Experiments Using Penalized Likelihood in Gaussian Kriging Models , 2005, Technometrics.
[25] Timothy M Wright,et al. Retrieval, experimental, and computational assessment of the performance of total knee replacements , 2006, Journal of orthopaedic research : official publication of the Orthopaedic Research Society.
[26] R. Rebonato,et al. The Most General Methodology to Create a Valid Correlation Matrix for Risk Management and Option Pricing Purposes , 2011 .
[27] V. Roshan Joseph,et al. Functionally Induced Priors for the Analysis of Experiments , 2007, Technometrics.
[28] Jerome Sacks,et al. Designs for Computer Experiments , 1989 .