Metadata-Version: 1.0
Name: acor
Version: 1.0.0
Summary: Estimate the autocorrelation time of a time series very quickly.
Home-page: http://github.com/dfm/acor/
Author: Daniel Foreman-Mackey and Jonathan Goodman
Author-email: danfm@nyu.edu
License: MIT
Description: 
        ACOR
        ====
        
        This is a direct port of a C++ routine by
        `Jonathan Goodman <http://www.math.nyu.edu/faculty/goodman/index.html>`_
        (NYU) called
        `ACOR <http://www.math.nyu.edu/faculty/goodman/software/acor/index.html>`_
        that estimates the autocorrelation time of time series data very quickly.
        
        `Dan Foreman-Mackey <http://danfm.ca>`_ (NYU) made a few surface changes to the
        interface in order to write a Python wrapper (with the permission of the original
        author).
        
        Installation
        ------------
        
        Just run ``pip install acor`` with the optional ``sudo`` if you need it. NumPy
        and the associated ``dev`` headers are needed.
        
        Usage
        -----
        
        Given some time series ``x``, you can estimate the autocorrelation time
        (``tau``) using::
        
            import acor
            tau, mean, sigma = acor.acor(x)
        
        References
        ----------
        
        * http://www.math.nyu.edu/faculty/goodman/software/acor/index.html
        * http://www.stat.unc.edu/faculty/cji/Sokal.pdf
        
        
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
