title: Estimated generalized least squares electromagnetic source analysis based on a parametric noise covariance model.
abstract: Estimated generalized least squares (EGLS) electromagnetic source analysis is used to downweight noisy and correlated data. Standard EGLS requires many trials to accurately estimate the noise covariances and, thus, the source parameters. Alternatively, the noise covariances can be modeled parametrically. Only the parameters of the model describing the noise covariances need to be estimated and, therefore, less trials are required. This method is referred to as parametric egls (PEGLS). In this paper, PEGLS is developed and its performance is tested in a simulation study and in a pseudoempirical study.
authors.affiliation: Department of Psychology, University of Amsterdam, The Netherlands. waldorp@psy.uva.nl
authors.forename: L J
authors.initials: LJ
authors.lastname: Waldorp
authors.forename: H M
authors.initials: HM
authors.lastname: Huizenga
authors.forename: C V
authors.initials: CV
authors.lastname: Dolan
authors.forename: P C
authors.initials: PC
authors.lastname: Molenaar
mesh_terms: D016009:Chi-Square Distribution; D003198:Computer Simulation; D004569:Electroencephalography; D006801:Humans; D016018:Least-Squares Analysis; D015225:Magnetoencephalography; D008433:Mathematics; D012815:Signal Processing, Computer-Assisted; D018709:Statistics, Nonparametric