gretta

Name	gretta JSON
Version	0.0.1 JSON
	download
home_page	https://github.com/recspert/gretta
Summary	Tensor-based SSA for sparse datasets with spatiotemporal information
upload_time	2023-10-21 08:46:25
maintainer
docs_url	None
author	Evgeny Frolov
requires_python
license
keywords
VCS
bugtrack_url
requirements	No requirements were recorded.
Travis-CI	No Travis.
coveralls test coverage	No coveralls.

            # GRETTA
**G**eneralized **RE**stricted **T**ensor **T**imeseries **A**nalysis.

This package is designed to perform multivariate analysis of incomplete timeseries based on the generalization of the restricted SSA method to sparse higher order (3D) data.
See an example on the analysis of spatiotemporal humidity data in the [Example-1.ipynb](Example-1.ipynb) jupyter notebook.

# Requirements
- numpy
- scipy
- pandas
- numba

# Citation
If you use `gretta` in published research, please cite:
> Frolov E, Oseledets I. 2023. Tensor-Based Sequential Learning via Hankel Matrix Representation for Next Item Recommendations. IEEE Access. 2023 Jan 5; 11:6357-71. DOI: [10.1109/ACCESS.2023.3234863](https://doi.org/10.1109/ACCESS.2023.3234863). arXiv: [2212.05720](https://arxiv.org/abs/2212.05720).

BibTex entry:
```
@ARTICLE{Frolov2023,
  author={Frolov, Evgeny and Oseledets, Ivan},
  journal={IEEE Access}, 
  title={Tensor-Based Sequential Learning via Hankel Matrix Representation for Next Item Recommendations}, 
  year={2023},
  volume={11},
  number={},
  pages={6357-6371},
  doi={10.1109/ACCESS.2023.3234863}}
```

            

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