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Merge pull request #100 from jvivian/jvivian/issue91
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Clean-up for 1.0 release
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jvivian authored Oct 28, 2024
2 parents 25e701f + be6471e commit 77b3866
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21 changes: 20 additions & 1 deletion README.md
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Expand Up @@ -23,14 +23,25 @@ Designed initially for evaluating the impacts of **COVID-19**, `DFMDash` is flex
- **Dynamic Factor Models**: Build models that combine pandemic and economic series to estimate latent variables representing pandemic intensity.
- **Drag-and-Drop**: Drop in files - options are then dynamically generated from the input data.


## Installation
There are multiple ways to run `DFMDash`,
There are multiple ways to install and run `DFMDash`.

> **Note**: Due to PyPI constraints, the example data files are stored on the GitHub repository rather than in the pip-installed package. If you wish to use `DFMDash` with the provided example data, please clone the repository and follow the installation steps below.
### Prerequisites

- Python 3.10+ is required.
- Tested environments: **Ubuntu**, **WSL2 (Windows)**, **MacOS** (M1 compatible).

### Option 0: Using Pip
> **Advanced:** If you have a Python environment set up, prefer to install via `pip` and _do not_ want/need the example data.
1. Install the package:
```bash
pip install dfmdash
```

### Option 1: Using Poetry

0. [Install Poetry](https://python-poetry.org/)
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## License

`DFMDash` is distributed under the MIT License. See [LICENSE](./LICENSE) for details.


# Citation
> If you use this tool in your research, please cite the following paper
```
Cooke, A., & Vivian, J. (2024). Pandemic Intensity Estimation using Dynamic Factor Modelling. Statistics, Politics and Policy. Manuscript under review.
```
16 changes: 8 additions & 8 deletions coverage.xml
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