A Python module that provides classes and functions for the estimation of many different statistical models, as well as for conducting statistical tests and statistical data exploration.
Statsmodels
- Python
- AI and Machine Learning, Data Analytics, Ecology and Sustainability, Mathematics, Quality
- Continuous Improvement, Machine Learning, Predictive Maintenance Algorithms, Statistical Analysis, Statistical Tests
Features:
- Linear regression models (OLS,GLS,WLS),generalized linear models (GLM),time series analysis (ARIMA,VAR,state-space models),econometric models,robust statistics,nonparametric statistics,survival analysis,hypothesis tests,plotting functions for statistical analysis,integration with pandas and NumPy
Pricing:
- Free
- Comprehensive library for statistical modeling and econometrics, provides detailed statistical output (summaries,diagnostics), good for users familiar with R's statistical capabilities, active development and good documentation.
- API can be less consistent than scikit-learn's for some models, learning curve for some of the more advanced statistical concepts and model interpretations, some overlap with SciPy.stats but generally more focused on modeling and econometrics.
Best for:
- Statisticians, econometricians, data scientists, and researchers performing in-depth statistical modeling, hypothesis testing, and time series analysis.