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International Journal of Mathematical Research

March 2018, Volume 7, 1, pp 1-17

Multivariate Analysis of EEG Data: Some Aspects of Diagnostic of MANOVA Model

Md Rokonuzzaman

Md Rokonuzzaman 1

  1. Associate Professor Department of Statistics University of Chittagong Chittagong-4331 Bangladesh 1

on Google Scholar
on PubMed

Pages: 1-17

DOI: 10.18488/journal.24.2018.71.1.17

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Article History:

Received: 07 September, 2017
Revised: 21 August, 2018
Accepted: 24 August, 2018
Published: 03 September, 2018


Abstract:

The main focus of this study is the multivariate analysis of Electroencephalogram data which included multivariate analysis of variance. The multivariate model diagnostics comprise checking number of assumptions of MANOVA model such as multivariate normality, homogeneity of covariance matrices. In this paper, the model X=BC+E is used and estimate the different parameters. Also by using a general form, H0: GBF=0 to test the different types of null hypothesis. Here G and F is known matrices and obtained from the hypothesis. This study gives mathematical ideas from multivariate statistical analysis to find a solution or a good approximation of a complex scientific problem.
Contribution/ Originality
This study gives mathematical ideas from multivariate statistical analysis to find a solution or a good approximation of a complex scientific problem.

Keywords:

Electroencephalogram, Fractal dimension, MANOVA.

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Statistics:

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Funding:

This study received no specific financial support.

Competing Interests:

The authors declare that they have no competing interests.

Acknowledgement:

I would like to express the deepest appreciation to Dr Tatjana von Rosen, Associate Professor, Stockholm University, Sweden who always gives me a great support in regard to this work.

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