Statistical learning and inference algorithms implemented in pure Python (version 3.6 or later).
The latest version of StatTools can be installed directly after cloning from GitHub:
git clone https://github.com/artemmavrin/StatTools.git
cd StatTools
make install
Moreover, StatTools is on the Python Package Index (PyPI), so a recent version of it can be installed with the pip utility:
pip install stattools
- Simple linear regression for fitting a line through a scatter plot
- Ridge regression
- Elastic net regularization (including LASSO and ridge regression as special cases)
- Fitting a polynomial curve to a scatter plot
- Various scatterplot smoothers applied to a sine curve with Gaussian noise
- Logistic regression for breast cancer diagnosis
- Multiclass logistic regression for handwritten digit recognition
- K-means clustering for grouping unlabelled data together
- Estimation of Gaussian mixture models
- Principal component analysis applied to handwritten digits
- Kernel density estimation for histogram smoothing
- The bootstrap (ordinary and Bayesian) and the jackknife for standard error estimation
- Bootstrap confidence intervals
- Exact and Monte Carlo permutation tests
- The Kaplan-Meier survivor function estimator