# DynamicESF
Author implementation of DynamicESF model, a computationally efficient spatially and temporally varying coefficient model. DynamicESF extends SVC (Spatially Varying Coefficient) models for space-time analysis.
## Install
` pip install DynamicESF `
See https://pypi.org/project/DynamicESF/ for detail.
## Examples
Check out [jupyter notebooks](https://github.com/hayato-n/DynamicESF/blob/main/examples).
## Reference
Please cite the following article.
Nishi, H., Asami, Y., Baba, H., & Shimizu, C. (2022). Scalable spatiotemporal regression model based on Moran’s eigenvectors. International Journal of Geographical Information Science, 1–27. https://doi.org/10.1080/13658816.2022.2100891
I recommend checking the following paper, which proposed the approximation method of Moran’s eigenvectors.
Murakami, D., & Griffith, D. A. (2019). Eigenvector Spatial Filtering for Large Data Sets: Fixed and Random Effects Approaches. Geographical Analysis, 51(1), 23–49. https://doi.org/10.1111/gean.12156
And R package spmoran (https://cran.r-project.org/web/packages/spmoran/index.html) will be helpful for R users.
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Release files for DynamicESF 0.1.1
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| File | Size | Uploaded | |
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| DynamicESF-0.1.1.tar.gz | 12.3 kB | Details |
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| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| DynamicESF-0.1.1-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 25.8 kB
Release files / DynamicESF-0.1.1.tar.gz
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Release files / DynamicESF-0.1.1-py3-none-any.whl
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