Goodness-of-fit tests in the context of estimation of brain evoked response parameter

• Autorzy: Gaura P.
• Konferencja: II Konferencja dla Młodych Matematyków. Zastosowania Matematyki -Lądek Zdrój 2001
• Języki publikacji: EN

Abstrakty

EN

The goal of the work described in the present paper is to assess the rightness of the assumption of a Gaussian brain noise distribution. Unfortunately, this noise always accompanies the brain evoked response examinations (e.g. MEG) and is a very significant part of a measured signal, so the knowledge of its nature is always desirable. In most works, the brain noise is cosidered to be Gaussian, however a convincing evidence that it should be so has not been presented yet. The assumption of the brain noise distribution determines brain response estimation, so the most accurate description of it seems to be very important.

• Wydawca: Oficyna Wydawnicza Politechniki Wrocławskiej
• Czasopismo: Prace Naukowe Instytutu Matematyki Politechniki Wrocławskiej. Konferencje
• Rocznik: 2003
• Tom: Vol. 25, nr 4
• Strony: 21--28
• Opis fizyczny: Bibliogr. 6 poz.

Twórcy

autor

Gaura P.

• Division of Measuring and Medical Electronic Devices, Faculty of Fundamental problems of Technology, Wrocław University of Technology , Poland.

Bibliografia

• [1] R.B. D'Agostino, M.A. Stephens, Goodness-of-fit Techniques (1986), Marcel Dekker Inc., New York.
• [2] P. Grzegorzewski, R Wieczorkowski, Testing Multivariate Normality - Experiments with Transformations (1999) Warsaw University of Technology, Faculty of Mathematics and Information Science, Preprint No 1.
• [3] J.C. de Munck, H.M. Huizenga, L.J. Waidorp, R.M. Heethaar, Estimating stationary dipoles from MEG/EEG data contaminated with spatially and temporally correlated background noise (2002) IEEE Trans. Sign. Proc., accepted.
• [4] P. Peterson, A.J. Stromberg, A Simple Test for Departures from Multivariate Normality (1998) Technical Report No 373, Department of Statistics, University of Kentucky http://www.ms.ukv.edu/~statinfo/techreports/tr373/tr373.html
• [5] J.P. Royston, An Extension of Shapiro-Willi''s Test for Normality to Large Samples, J. Appl. Statist. 31 (1982), 115-124.
• [6] S.S. Shapiro, M.B. Wilk, An analysis of variance test for normality (complete samples), Biometrika 52 (1965), 591-611.