SCM: Sample Covariance Matrix
In LauraMasiero/RiemannR: RiemannR - EEG-based BCI analysis with Riemannian geometry
Description
Usage
Arguments
Value
Author(s)
References
Description
This function creates a sample covariance matrix from an EEG trial matrix.
Usage
1
SCM(x)
Arguments
x
a nxt numeric matrix, where n indicates the number of recording channels and t indicates the time points.
Value
It returns a sample covariance matrix.
Author(s)
Laura Masiero, email: laura.masiero.10@gmail.com
References
Barachant, Alexandre, Stéphane Bonnet, Marco Congedo e Christian Jutten (2012). "Multiclass brain-computer interface classification by Riemannian geometry". In: IEEE Transactions on Biomedical Engineering. doi: 10.1109/TBME.2011.2172210.
LauraMasiero/RiemannR documentation built on Sept. 29, 2020, 9:51 p.m.
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Description Usage Arguments Value Author(s) References
Description
This function creates a sample covariance matrix from an EEG trial matrix.
Usage
1 | SCM(x)
|
Arguments
x |
a nxt numeric matrix, where n indicates the number of recording channels and t indicates the time points. |
Value
It returns a sample covariance matrix.
Author(s)
Laura Masiero, email: laura.masiero.10@gmail.com
References
Barachant, Alexandre, Stéphane Bonnet, Marco Congedo e Christian Jutten (2012). "Multiclass brain-computer interface classification by Riemannian geometry". In: IEEE Transactions on Biomedical Engineering. doi: 10.1109/TBME.2011.2172210.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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