==================================================================== Gamaleldin F. Elsayed, Columbia University
John P. Cunningham, Columbia University
Copyright (C) 2017 Gamaleldin F. Elsayed and John P. Cunningham
This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.
This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.
You should have received a copy of the GNU General Public License along with this program. If not, see http://www.gnu.org/licenses/.
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==================================================================== Basic Usage Example
Follow the demo.m file
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==================================================================== TME
This code package is for the Tensor-Maximum-Entropy (TME) method. This method generates random surrogate data that preserves a specified set of first and second order marginal moments of a data tensor, which makes it well equipped to test for the null hypothesis that a structure in data is an epiphenomenon of these specified set of primary features of the data tensor. The random surrogate data are sampled from a maximum entropy distribution. This distribution unlike traditional maximum entropy method have constraints on the marginal first and second moments of the tensor mode.
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The BibTeX citations for the primary papers used in this project are:
@article{elsayed, title={Structure in neural population recordings: an expected byproduct of simpler phenomena?}, author={Gamaleldin Elsayed, John Cunningham}, journal={Nature Neuroscience}, volume={}, year={} }
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