https://github.com/dalawey/deming_regression

https://github.com/dalawey/deming_regression

Science Score: 13.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • CITATION.cff file
  • codemeta.json file
    Found codemeta.json file
  • .zenodo.json file
  • DOI references
  • Academic publication links
  • Academic email domains
  • Institutional organization owner
  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (7.3%) to scientific vocabulary
Last synced: 6 months ago · JSON representation

Repository

Basic Info
  • Host: GitHub
  • Owner: dalawey
  • License: mit
  • Language: Python
  • Default Branch: main
  • Size: 7.81 KB
Statistics
  • Stars: 0
  • Watchers: 1
  • Forks: 0
  • Open Issues: 0
  • Releases: 0
Created over 1 year ago · Last pushed over 1 year ago
Metadata Files
Readme License

README.md

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 demingregression import demingregression 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.

Owner

  • Login: dalawey
  • Kind: user

GitHub Events

Total
Last Year

Packages

  • Total packages: 1
  • Total downloads:
    • pypi 14 last-month
  • Total dependent packages: 0
  • Total dependent repositories: 0
  • Total versions: 1
  • Total maintainers: 1
pypi.org: demingfit

A package for performing Deming regression

  • Versions: 1
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Downloads: 14 Last month
Rankings
Dependent packages count: 10.4%
Average: 34.6%
Dependent repos count: 58.8%
Maintainers (1)
Last synced: 6 months ago

Dependencies

setup.py pypi
  • numpy *
  • pandas *