@techreport{d8c37ad3f9a54824986d274bf7fe91bb,

title = "White Noise Assumptions Revisited: Regression Models and Statistical Designs for Simulation Practice",

abstract = "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 these classic assumptions in simulation practice?(ii) How can these assumptions be tested? (iii) If assumptions are violated, can the simulation's I/O data be transformed such that the assumptions hold?(iv) If not, which alternative statistical methods can then be applied?",

keywords = "metamodels, experimental designs, generalized least squares, multivariate analysis, normality, jackknife, bootstrap, heteroscedasticity, common random numbers, validation",

author = "J.P.C. Kleijnen",

note = "Pagination: 21",

year = "2006",

language = "English",

volume = "2006-50",

series = "CentER Discussion Paper",

publisher = "Operations research",

type = "WorkingPaper",

institution = "Operations research",

}