likefit

Name	likefit JSON
Version	0.2.2 JSON
	download
home_page	None
Summary	Fit data with least squares and other likelihood methods
upload_time	2024-06-12 18:05:32
maintainer	None
docs_url	None
author	None
requires_python	>=3.8
license	MIT License Copyright (c) 2024 Diego Ravignani Guerrero Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
keywords	fit likelihood scipy
VCS
bugtrack_url
requirements	No requirements were recorded.
Travis-CI	No Travis.
coveralls test coverage	No coveralls.

            # LikeFit

LikeFit is a library to fit data for science and engineering. 
It provides a user-friendly and comprehensive interface for linear and non-linear least squares, and likelihood fits.


## Install

```sh
python -m pip install likefit
```

## Features
  * Linear and nonlinear least squares fit with a consistent interface
  * Fit of histograms with a Poisson likelihood
  * Calculation of estimators, errors, and correlations
  * Evaluation of goodness-of-fit with chi-squared test
  * Plot of error bands, confidence regions, and likelihood functions

## How to use
These [demos](https://github.com/ravignad/likefit_demos.git) contain Jupyter notebooks that show how to use the LikeFit library.

## Contributing
If you want to contribute, please fork the repository and use a feature
branch. Pull requests are warmly welcome.

## Links
- Repository: https://github.com/ravignad/likefit/
- Demos: https://github.com/ravignad/likefit_demos.git

## Licensing
The code in this project is licensed under MIT license.

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