Metadata-Version: 2.1
Name: demingfit
Version: 0.1.0
Summary: A package for performing Deming regression
Home-page: https://github.com/dalawey/deming_regression.git
Author: Dalawey Chen
Project-URL: Bug Tracker, https://github.com/dalawey/deming_regression/issues
Project-URL: Documentation, https://github.com/dalawey/deming_regression/wiki
Project-URL: Source Code, https://github.com/dalawey/deming_regression
Keywords: deming regression statistics data-analysis
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Topic :: Scientific/Engineering :: Mathematics
Requires-Python: >=3.7
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: pandas>=1.0.0
Requires-Dist: numpy>=1.18.0

# Deming Regression

This package provides a simple implementation of Deming regression, an errors-in-variables model which tries to find the line of best fit for a two-dimensional dataset when there are errors in both the x and y variables.

## Installation

You can install the package using pip:

```
pip install deming_regression
```

## Usage

Here's a simple example of how to use the `deming_regression` function:

```python
from deming_regression import deming_regression
import numpy as np

x = np.array([1, 2, 3, 4, 5])
y = 2 * x + 1 + np.random.normal(0, 0.1, 5)

intercept, slope = deming_regression(x, y, 0.1, 0.1)
print(f"Intercept: {intercept}, Slope: {slope}")
```

## Running Tests

To run the unit tests, navigate to the package directory and run:

```
python -m unittest discover tests
```

## License

This project is licensed under the MIT License.
