Metadata-Version: 2.1
Name: stattools
Version: 0.0.4
Summary: Statistical learning and inference library
Home-page: https://github.com/artemmavrin/StatTools
Author: Artem Mavrin
Author-email: amavrin@ucsd.edu
License: MIT
Description: # StatTools
        
        [![PyPI version](https://badge.fury.io/py/stattools.svg)](https://badge.fury.io/py/stattools)
        
        Statistical learning and inference algorithms implemented in pure Python (version 3.6 or later).
        
        ## Installation
        
        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)](https://pypi.org/project/stattools/), so a recent version of it can be installed with the `pip` utility:
        
            pip install stattools
        
        ## Dependencies
        
        * [NumPy](http://www.numpy.org)
        * [SciPy](https://www.scipy.org)
        * [pandas](https://pandas.pydata.org)
        * [Matplotlib](https://matplotlib.org)
        
        ## Examples
        
        ### Regression
        
        * [Simple linear regression for fitting a line through a scatter plot](https://github.com/artemmavrin/StatTools/blob/master/examples/Simple%20Linear%20Regression.ipynb)
        * [Ridge regression](https://github.com/artemmavrin/StatTools/blob/master/examples/Ridge%20Regression.ipynb)
        * [Elastic net regularization (including LASSO and ridge regression as special cases)](https://github.com/artemmavrin/StatTools/blob/master/examples/Elastic%20Net.ipynb)
        * [Fitting a polynomial curve to a scatter plot](https://github.com/artemmavrin/StatTools/blob/master/examples/Polynomial%20Smoothing.ipynb)
        * [Various scatterplot smoothers applied to a sine curve with Gaussian noise](https://github.com/artemmavrin/StatTools/blob/master/examples/Scatterplot%20Smoothers.ipynb)
        
        ### Classification
        
        * [Logistic regression for breast cancer diagnosis](https://github.com/artemmavrin/StatTools/blob/master/examples/Logistic%20Regression.ipynb)
        * [Multiclass logistic regression for handwritten digit recognition](https://github.com/artemmavrin/StatTools/blob/master/examples/Multiclass%20Logistic%20Regression.ipynb)
        
        ### Unsupervised Learning
        
        * [K-means clustering for grouping unlabelled data together](https://github.com/artemmavrin/StatTools/blob/master/examples/K-Means%20Clustering.ipynb)
        * [Estimation of Gaussian mixture models](https://github.com/artemmavrin/StatTools/blob/master/examples/Gaussian%20Mixture%20Models.ipynb)
        * [Principal component analysis applied to handwritten digits](https://github.com/artemmavrin/StatTools/blob/master/examples/Principal%20Component%20Analysis.ipynb)
        * [Kernel density estimation for histogram smoothing](https://github.com/artemmavrin/StatTools/blob/master/examples/Kernel%20Density%20Estimation.ipynb)
        
        ### Non-Parametric Statistics
        
        * [The bootstrap (ordinary and Bayesian) and the jackknife for standard error estimation](https://github.com/artemmavrin/StatTools/blob/master/examples/Bootstrap%20and%20Jackknife.ipynb)
        * [Bootstrap confidence intervals](https://github.com/artemmavrin/StatTools/blob/master/examples/Bootstrap%20Confidence%20Intervals.ipynb)
        * [Exact and Monte Carlo permutation tests](https://github.com/artemmavrin/StatTools/blob/master/examples/Permutation%20Test.ipynb)
        * [The Kaplan-Meier survivor function estimator](https://github.com/artemmavrin/StatTools/blob/master/examples/Kaplan-Meier%20Estimator.ipynb)
        
        ### Ensemble Methods
        
        * [Using bagging to improve logistic regression accuracy](https://github.com/artemmavrin/StatTools/blob/master/examples/Bagging%20Logistic%20Regression.ipynb)
        
        ### Data Visualization
        
        * [Plotting lines and function curves](https://github.com/artemmavrin/StatTools/blob/master/examples/Plotting%20Lines%20and%20Functions.ipynb)
        * [Drawing empirical distribution functions](https://github.com/artemmavrin/StatTools/blob/master/examples/Empirical%20Distribution%20Functions.ipynb)
        * [Drawing quantile-quantile (QQ) plots](https://github.com/artemmavrin/StatTools/blob/master/examples/Quantile-Quantile%20Plots.ipynb)
        
        ### Simulation
        
        * [Simulating sample paths of Poisson processes](https://github.com/artemmavrin/StatTools/blob/master/examples/Poisson%20Process.ipynb)
        * [Simulating sample paths of Itô diffusions (for example, Brownian motion)](https://github.com/artemmavrin/StatTools/blob/master/examples/Ito%20Diffusions.ipynb)
        
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