Metadata-Version: 2.1
Name: fattails
Version: 0.0.3
Summary: A package for fat-tailed statistics
Home-page: https://github.com/FergM/fattails/
Author: FergM
License: UNKNOWN
Description: # Fat Tails
        Python package and Jupyter notebooks for fat-tailed statistics. Inspired by Nassim Taleb's Technical Incerto.
        
        <div>
          <a href="https://pypi.org/project/fattails">
              <img src="https://badge.fury.io/py/fattails.svg" alt="package version"/>
          </a>
        </div>
        
        ## Content
        
        ### Notebooks
        See the [notebooks/README.md](./notebooks/) for more detail.
        
        My favourite notebooks so far:
        * [Central Limit Theorem: How the sum of Uniform values is Gaussian](./notebooks/NB-22%20-%20Visual%20Central%20Limit%20Theorem.ipynb)
        * [S&P500: How geometric average return is impossible](./notebooks/Notebook-11%20-%20Ergodicity%20and%20S%26P500.ipynb)
        * [GameStop: January 2021 was not an outlier if you assume Power Law tails.](./notebooks/NB-25%20-%20Survival%20Plot%20-%20Gamestop.ipynb)
        
        ### Functions
        Quick Access:
        * `fattails.mad()`: Calculates mean absolute deviation.
        Other:
        * `fattails.metrics.get_survival_probability()`: Calculate survival probabilities for a given dataset.
        
        Example:
        ```
        $ pip install fattails
        $ python
        
        >>> import fattails
        >>>
        >>>
        >>> fattails.mad([1,2,3]) # Calculate Mean Absolute Deviation of [1,2,3]
        0.6666666666666666
        >>>
        >>>
        >>> fattails.metrics.get_survival_probability([1,2,3]) # Get survival probability for each value in your data
        0    0.75
        1    0.50
        2    0.25
        Name: survival_probability, dtype: float64
        ```
        
        ### Derivations
        * [How much data do I need?](/docs/Notes-02%20-%20Derivation%20-%20How%20much%20data%20do%20I%20need.pdf)
        
        # External Resources
        Technical Incerto Book One:
        * [PDF on researchers.one](https://researchers.one/articles/20.01.00018)
        * [PDF on arxiv.org](https://arxiv.org/abs/2001.10488)
        * [Errata](https://www.fooledbyrandomness.com/Errata2020FirstEdition.pdf)
        
        More Links:
        * Incerto Reading Club: [Website](http://www.techincertoreadingclub.com/), [GitHub](https://github.com/Technical-Incerto-Reading-Club/code-examples)
        * [`StatisticalConsequencesOfFatTails`](https://github.com/MarcosCarreira/StatisticalConsequencesOfFatTails): Code and Links collected by [Marcos Carreira](https://github.com/MarcosCarreira)
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.8.5
Description-Content-Type: text/markdown
