This release is a pre-release and may not be stable for production use.
A Robust and Efficient Method to Find Profile Likelihood Confidence Intervals
This package provides an implementation of a robust and efficient method to compute profile likelihood confidence intervals developed by Fischer and Lewis (2021). If you use this package in research that leads to a scientific publication, we kindly ask you to cite the paper.
The package is licensed under the LGPL-v3. For documentation please refer to the project's documentation page on github. Please report any bugs on the project's bug tracker. You are welcome to adjust the provided files to your needs and to improve the code. It is encouraged that you share any improvements on the github page if possible.
1 maintainer
Metadata
1 maintainer
Release files for ci-rvm 0.10.1b3
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 | |
|---|---|---|---|---|
| ci_rvm-0.10.1b3.tar.gz | 54.8 kB | Without provenance | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| ci_rvm-0.10.1b3-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 109.1 kB
Release files / ci_rvm-0.10.1b3.tar.gz
| Download URL | ci_rvm-0.10.1b3.tar.gz |
|---|---|
| Size | 54.8 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
7a5829714cf30aa69c02d447fa31fe470e2ae45adb01d204d17ae0abf7fbc22f
|
|
BLAKE2b-256 checksum How to use checksums |
8fcd8ea3c16ceb9e4f2ccae25835fab042c79a610add823b684d44bddcb01b23
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.2 CPython/3.11.0
|
Release files / ci_rvm-0.10.1b3-py3-none-any.whl
| Download URL | ci_rvm-0.10.1b3-py3-none-any.whl |
|---|---|
| Size | 54.3 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
85104e6f61542a131898644b90a68cf1aa96d69e460243b2b0b3901fc68c2f1b
|
|
BLAKE2b-256 checksum How to use checksums |
f6732887a49ba8603b30a1b73631181db98615fac005243d006ad0d8f7009be6
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.2 CPython/3.11.0
|
Security for ci-rvm 0.10.1b3
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.
