Orthogonal arrays for estimating global sensitivity indices of non-parametric models based on ANOVA high-dimensional model representation
From MaRDI portal
Publication:419288
DOI10.1016/j.jspi.2012.02.043zbMath1237.62097OpenAlexW1986884291MaRDI QIDQ419288
Ying-Shan Zhang, Yin-cai Tang, Xiao-Di Wang
Publication date: 18 May 2012
Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.jspi.2012.02.043
Optimal statistical designs (62K05) Orthogonal arrays, Latin squares, Room squares (05B15) Analysis of variance and covariance (ANOVA) (62J10)
Related Items
Orthogonal arrays robust to a specified set of nonnegligible effects ⋮ \(A\)-optimal designs for non-parametric symmetrical global sensitivity analysis ⋮ Feasible criterion for designs based on fixed effect ANOVA model ⋮ A screening approach for non-parametric global sensitivity analysis ⋮ General orthogonal designs for parameter estimation of ANOVA models under weighted sum-to-zero constraints ⋮ An analytical structural global sensitivity analysis method based on direct integral
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Variance based sensitivity analysis of model output. Design and estimator for the total sensitivity index
- Orthogonal arrays with variable numbers of symbols
- The jackknife estimate of variance
- Optimality of certain asymmetrical experimental designs
- The effective dimension and quasi-Monte Carlo integration
- Quasi-regression with shrinkage
- Sampling plans based on balanced incomplete block designs for evaluating the importance of computer model inputs
- Large Sample Properties of Simulations Using Latin Hypercube Sampling
- Latin supercube sampling for very high-dimensional simulations
- Monte Carlo estimators for small sensitivity indices
- A Class of Statistics with Asymptotically Normal Distribution
- Global sensitivity indices for nonlinear mathematical models and their Monte Carlo estimates
