Draft:Phitter
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| Phitter | |
|---|---|
 | |
 | |
| Repository | GitHub Repository |
| Written in | Python |
| Operating system | Cross-platform (Windows, macOS, Linux) |
| Platform | Web application |
| Available in |
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| Type | Statistical software |
| License | MIT License |
| Website | Phitter |
Phitter is an open-source Python library designed to streamline the process of fitting and analyzing probability distributions for applications in statistics, data science, operations research, and machine learning. It provides a comprehensive catalog of over 80 continuous and discrete distributions, multiple goodness-of-fit measures (Chi-Square, Kolmogorov-Smirnov, and Anderson-Darling), interactive visualizations for exploratory data analysis and model validation, and detailed modeling guides with spreadsheet implementations. By reducing the complexity of distribution fitting, Phitter helps researchers and practitioners identify distributions that best model their data.[1][2][3]
Features
[edit]Phitter supports fitting over 80 continuous and discrete probability distributions and includes the following features:
- Documentations, spreadsheets and python support for continuous and discrete distributions[4]
- Web-based interface and Python library[5]
- Goodness-of-fit tests: Chi-square, Kolmogorov–Smirnov, Anderson–Darling[6]
- Interactive visualizations: PDF overlays, CDF plots, Q–Q plots[7]
- Automated modeling reports with formulas and parameter estimates
- Simulation tools for stochastic processes and queueing systems (e.g., FIFO, LIFO)
- Parallel processing for large datasets
- Open-source under the MIT License
See also
[edit]References
[edit]- ^ Monterrosa, Sebastián José Herrera; Pinilla, Carlos Andrés Masmela (2025). "Phitter: A library designed to streamline the process of fitting and analyzing probability distributions". Journal of Open Source Software. 10 (110): 7625. doi:10.21105/joss.07625.
- ^ "Univariate Distribution Relationships". William & Mary Department of Mathematics. Retrieved 2025-06-16.
- ^ "Phitter – A Python library for statistical distribution fitting". Reddit. 3 January 2025. Retrieved 2025-06-16.
- ^ "Playground continuous and discrete distributions". Phitter. Retrieved 2025-06-16.
- ^ "Phitter Documentation". Phitter Docs. Retrieved 2025-06-16.
- ^ "How to Use Goodness-of-Fit Tests to Validate Your Distribution Choice in Phitter". Statology. 27 February 2025. Retrieved 2025-06-16.
- ^ "How to Use ECDF Analysis to Validate Distribution Fits in Phitter". Statology. 28 February 2025. Retrieved 2025-06-16.
Category:Statistical software Category:Free statistical software Category:Python (programming language) libraries Category:Free software programmed in Python Category:Cross-platform software