Python CovRegpy Package
Regularised covariance regression software based on Hoff and Niu (2012) - see https://arxiv.org/pdf/1102.5721.
This package was developed out of research performed by Cole van Jaarsveldt, Gareth W. Peters, Matthew Ames, and Mike Chantler. This package was built entirely using Python 3.11.5 - Python guarantees backwards compatibility which should ensure that this software package functions as expected on all future Python versions. See:
van Jaarsveldt, C., Peters, G., Ames, M., & Chantler, M. (2024) Package CovRegpy: Regularized covariance regression and forecasting in Python. Annals of Actuarial Science, First View. doi:10.1017/S1748499524000101 url: https://dx.doi.org/10.1017/S1748499524000101
Metadata
Release files for CovRegpy 0.0.7
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| CovRegpy-0.0.7.tar.gz | 25.4 kB | Without provenance | Details for CovRegpy-0.0.7.tar.gz |
Release files / CovRegpy-0.0.7.tar.gz
| Download URL | CovRegpy-0.0.7.tar.gz |
|---|---|
| Size | 25.4 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
63f6c20c231f3f0f85b52f1294bb4bef114cf95d2cb410e2e5456380c7e85544
|
|
BLAKE2b-256 checksum How to use checksums |
6afa27a129eb0f5c097446d410a5ae2d57b768326435b98f8c49e9fba2e3683c
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.2 CPython/3.7.4
|
Security for CovRegpy 0.0.7
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
No provenance found
None of the files in this release were uploaded with provenance metadata.
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
To learn more about protecting yourself from malicious actors, visit our package security documentation.