Smooth data across multiple dimensions using weighted averages
Project description
Weighted-Average (WeAve)
The WeAve package (pronounced 'weave') smooths data across multiple dimensions using weighted averages with methods inspired by the spatial-temporal models developed in the following paper:
Foreman, K.J., Lozano, R., Lopez, A.D., et al. "Modeling causes of death: an integrated approach using CODEm," Popul Health Metrics, vol. 10, no. 1, pp. 1-23, 2012.
For instructions on how to install and use WeAve, please refer to the documentation.
License
This project uses the following license: BSD 2-Clause
Project details
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
weighted-average-1.1.0.tar.gz
(15.5 kB
view hashes)
Built Distribution
Close
Hashes for weighted_average-1.1.0-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 007ff00e7df9151386f1fddd9590ee741e5637d1acedf23a9c05894a7fde9893 |
|
MD5 | 0a38f66e0184d4d6ccd986ccad2b16b7 |
|
BLAKE2b-256 | 8cd834f078aa91343d4576da81a2a931e38cc9e225bb790e8dbef0749091adc7 |