F
Fetsje Bijma
Researcher at VU University Amsterdam
Publications - 29
Citations - 618
Fetsje Bijma is an academic researcher from VU University Amsterdam. The author has contributed to research in topics: Covariance & Covariance matrix. The author has an hindex of 11, co-authored 28 publications receiving 577 citations. Previous affiliations of Fetsje Bijma include Vanderbilt University Medical Center & University of Amsterdam.
Papers
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Journal ArticleDOI
In vivo measurement of the brain and skull resistivities using an EIT-based method and realistic models for the head
S.I. Gonçalves,J.C. de Munck,J.P.A. Verbunt,Fetsje Bijma,Rob M. Heethaar,F.H. Lopes da Silva +5 more
TL;DR: Results demonstrate that /spl rho//sub skull/ is more likely to be within 20 and 50 rather than equal to the commonly accepted value of 80, and the correction for geometry errors is essential to obtain realistic estimations.
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The spatiotemporal MEG covariance matrix modeled as a sum of Kronecker products
TL;DR: The single Kronecker product (KP) model for the spatiotemporal covariance of MEG residuals is extended to a sum of Kr onecker products such that it approximates the spatiotsemporal sample covariance best in matrix norm.
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A maximum-likelihood estimator for trial-to-trial variations in noisy MEG/EEG data sets
TL;DR: A maximum-likelihood estimator is derived for the case that the recorded data contain amplitude variations and is applied to a series of 17 MEG data sets of normal subjects, where it appears that the amplitude of late component shows a systematic negative trend indicating a weakening response during stimulation time.
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A mathematical approach to the temporal stationarity of background noise in MEG/EEG measurements.
TL;DR: It appears that very good agreement between the data and the parametric model can be obtained when the baseline correction window is taken into account properly, implying that the background noise is in principle a stationary process and that nonstationarities are mainly caused by the nature of the preprocessing method.
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Existence and uniqueness of the maximum likelihood estimator for models with a Kronecker product covariance structure
TL;DR: This paper investigates whether the maximum likelihood estimator of the covariance matrix exists and whether it is unique, and considers models with general, with double diagonal, and with one diagonal Kronecker product covariance matrices, and finds different results.