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        "description": "PySSM: A Python Module for Bayesian Inference of Linear Gaussian State Space Models.\n====================================================================================\n**Authors**: Strickland C. M, Burdett R. L., Mengerson K. L, Denham R. J.\n\nPySSM is a Python package that has been developed for the analysis of\ntime series using linear Gaussian state space models (SSM).\n\nPySSM is easy to use; models can be set up quickly and efficiently and\na variety of different settings are available to the user.  It also\ntakes advantage of scientific libraries Numpy and Scipy and other\nhigh level features of the Python language.\n\nPySSM default is also used as a platform for interfacing between\noptimised and parallelised FORTRAN routines.  These FORTRAN routines\nheavily utilise Basic Linear Algebra (BLAS) and Linear Algebra Package\n(LAPACK) functions for maximum performance.\n\nPySSM contains classes for filtering, classical smoothing as well as\nsimulation smoothing.\n\nYou can access the code from the `git repository\n<https://bitbucket.org/christophermarkstrickland/pyssm>`_ and submit\nbugs/requests viat `the issue\ntracker. <https://bitbucket.org/christophermarkstrickland/pyssm/issues/>`_",
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