’s (2003) and in some simulation examples we consider, we find that our test can be more powerful than the subsampling test of …

is conducted. The results show that the proposed GCIs approach is superior to the standard bootstrap in terms of coverage …

research by using of a leveraged bootstrap test developed by Hacker and Hatemi-J (2006) to examine the behavior of the …

This article uses a sequentialized experimental design to select simulation input combinations for global optimization …/output data of the simulation model (computer code). This design and analysis adapt the classic “expected improvement” (EI) in …

- ceptable. The methodology combines simulation, bootstrapping, and metamodeling. The methodology is illustrated through a …-factorial design. The resulting simulation In- put/Output (I/O) data are analyzed through a first-order polynomial metamodel and …

combination of the following four proven techniques: (1) discrete-event simulation, (2) heuristic optimization, (3) risk or …

The bootstrap is a simple but versatile technique for the statistical analysis of random simulations.This tutorial … explains the basics of that technique, and applies it to the well-known M/M/1 queuing simulation.In that numerical example …

combination of simulation inputs not yet simulated? (2) How to select the next combination to be simulated when searching for the … optimal combination? To answer these questions, the paper uses parametric bootstrapped Kriging and "conditional simulation …

This paper proposes a novel method to select an experimental design for interpolation in random simulation.(Though the ….)Assuming that simulation requires much computer time, it is important to select a design with a small number of observations (or … simulation runs).The proposed method is therefore sequential.Its novelty is that it accounts for the specific input …