Add to ORKGLink to publication Citation for published version (APA): Dellino, G., Kleijnen, J. P. C., & Meloni, C. (2010). Parametric and distribution-free bootstrapping in robus
Available from Centro de Informacion y Documentacion Cientifica CINDOC. Joaquin Costa, 22. 28002 Mad...
The bootstrap is a powerful non-parametric statistical technique for making probability-based infere...
AbstractMost methods in simulation-optimization assume known environments, whereas this research acc...
Most methods in simulation-optimization assume known environments, whereas this research accounts fo...
Kriging (or Gaussian Process) metamodels may be analyzed through bootstrapping, which is a versatile...
This survey considers the optimization of simulated systems. The simulation may be either determinis...
Abstract: This article surveys optimization of simulated systems. The simulation may be either deter...
This article surveys optimization of simulated systems. The simulation may be either deterministic o...
International audienceThe bootstrap is a technique for performing statistical inference. The underly...
Most methods in simulation-optimization assume known environments, whereas this research accounts fo...
Metamodels are often used in simulation-optimization for the design and management of complex system...
this article. 4. BOOTSTRAP SIMULATION METHOD 4.1. General Consider that a random sample of observ...
This contribution summarizes a methodology for simulation optimization assuming some simulation inp...
This article uses a sequentialized experimental design to select simulation input combinations for g...
This contribution summarizes a methodology for simulation optimization assuming some simulation inpu...
Available from Centro de Informacion y Documentacion Cientifica CINDOC. Joaquin Costa, 22. 28002 Mad...
The bootstrap is a powerful non-parametric statistical technique for making probability-based infere...
AbstractMost methods in simulation-optimization assume known environments, whereas this research acc...
Most methods in simulation-optimization assume known environments, whereas this research accounts fo...
Kriging (or Gaussian Process) metamodels may be analyzed through bootstrapping, which is a versatile...
This survey considers the optimization of simulated systems. The simulation may be either determinis...
Abstract: This article surveys optimization of simulated systems. The simulation may be either deter...
This article surveys optimization of simulated systems. The simulation may be either deterministic o...
International audienceThe bootstrap is a technique for performing statistical inference. The underly...
Most methods in simulation-optimization assume known environments, whereas this research accounts fo...
Metamodels are often used in simulation-optimization for the design and management of complex system...
this article. 4. BOOTSTRAP SIMULATION METHOD 4.1. General Consider that a random sample of observ...
This contribution summarizes a methodology for simulation optimization assuming some simulation inp...
This article uses a sequentialized experimental design to select simulation input combinations for g...
This contribution summarizes a methodology for simulation optimization assuming some simulation inpu...
Available from Centro de Informacion y Documentacion Cientifica CINDOC. Joaquin Costa, 22. 28002 Mad...
The bootstrap is a powerful non-parametric statistical technique for making probability-based infere...
AbstractMost methods in simulation-optimization assume known environments, whereas this research acc...