{"repo":"erdogant/distfit","free":true,"listed":false,"github":"https://github.com/erdogant/distfit","clone":"git clone https://github.com/erdogant/distfit.git","description":"distfit is a python library for probability density fitting.","language":"Jupyter Notebook","stars":423,"topics":["probability-distribution","fitting-curve","hypothesis-testing","sse","probability-statistics","pdf","density-functions","pypi","cumulative-distribution-function","kolmogorov-smirnov"],"license":null,"category":"media-processing","readme_excerpt":"distfit is a Python package for probability density fitting of univariate distributions for random variables. The distfit library can determine the best fit for over 90 theoretical distributions. The goodness-of-fit test is used to score for the best fit and after finding the best-fitted theoretical distribution, the loc, scale, and arg parameters are returned. It can be used for parametric, non-parametric, and discrete distributions. ⭐️Star it if you like it⭐️ --- Key Features Feature Description Medium Gumroad+Podcast --------- ------------- -------- ----------------- Parametric Fitting Fit distributions on empirical data X. Link Link Non-Parametric Fitting Fit distributions on empirical data X using non-parametric approaches (quantile, percentiles). - - Multivariate Fitting Fit multivariate distributions on empirical data X that contains multiple columns. - - Discrete Fitting Fit distributions on empirical data X using binomial distribution. - - Predict Compute probabilities for response variables y. - - Outlier Detection Detect anomalies using fitted distributions. Link Link Synthetic Data Generate synthetic data. Link Link Plots Various plotting functionalities. - - --- Resources and Links - Example Notebooks: Examples - Medium Blogs Medium - Gumroad Blogs with podcast: GumRoad - Documentation: Website - Bug Reports and Feature Requests: GitHub Issues --- Background For the parametric approach, The distfit library can determine the best fit across 89 theoretical distribu","default_branch":null,"files":null,"tree":[],"storefront":"/r/erdogant","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/erdogant/distfit/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}