A multivariate non-parametric kernel estimator for global sensitivity analysis
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Publication:5084941
DOI10.1080/03610918.2017.1309430OpenAlexW2601794480MaRDI QIDQ5084941
Tristan Senga Kiessé, Smail Adjabi, Lamia Djerroud
Publication date: 29 June 2022
Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/03610918.2017.1309430
Nonparametric regression and quantile regression (62G08) Estimation in multivariate analysis (62H12)
Cites Work
- Unnamed Item
- Uncertainty management in simulation-optimization of complex systems. Algorithms and applications
- A Bayesian approach to bandwidth selection for multivariate kernel density estimation
- A sampling algorithm for bandwidth estimation in a nonparametric regression model with a flexible error density
- Mastering uncertainty in industry. I: A global methodological approach based on examples
- Effects of associated kernels in nonparametric multiple regressions
- A Bayesian approach to bandwidth selection for multivariate kernel regression with an application to state-price density estimation
- Remarks on Some Nonparametric Estimates of a Density Function
- THE UNIQUENESS OF CROSS-VALIDATION SELECTED SMOOTHING PARAMETERS IN KERNEL ESTIMATION OF NONPARAMETRIC MODELS
- Equation of State Calculations by Fast Computing Machines
- A review on global sensitivity analysis methods
- Probability Inequalities for Sums of Bounded Random Variables
- Bayesian Approach in Nonparametric Count Regression with Binomial Kernel
- Discrete triangular distributions and non-parametric estimation for probability mass function
- Monte Carlo sampling methods using Markov chains and their applications
- Global sensitivity indices for nonlinear mathematical models and their Monte Carlo estimates
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