Classic linear regression models and their concomitant statistical designs assume a univariate response and white noise.By definition, white noise is normally, independently, and identically distributed with zero mean.This survey tries to answer the following questions: (i) How realistic are...

Generalized Response Surface Methodology (GRSM) is a novel general-purpose metaheuristic based on Box and Wilson.s Response Surface Methodology (RSM).Both GRSM and RSM estimate local gradients to search for the optimal solution.These gradients use local first-order polynomials.GRSM, however,...

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, different responses are studied.For some responses,...

In practice, simulation analysts often change only one factor at a time, and use graphical analysis of the resulting Input/Output (I/O) data. The goal of this article is to change these traditional, naïve methods of design and analysis, because statistical theory proves that more information is...

In practice, simulation analysts often change only one factor at a time, and use graphical analysis of the resulting Input/Output (I/O) data. Statistical theory proves that more information is obtained when applying Design Of Experiments (DOE) and linear regression analysis. Unfortunately,...

We look at the contribution of various income components on income inequality and the changes in this in Belgium.Starting from the Shorrocks decomposition, we apply bootstrapping to construct confidence intervals for both the annual decomposition and the changes over time.It appears that the...