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DynamicESF: fast spatially and temporally varying coefficient model

Project description

# 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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