PySSM: A Python Module for Bayesian Inference of Linear Gaussian State Space Models.

Authors: Strickland C. M, Burdett R. L., Mengerson K. L, Denham R. J.

PySSM is a Python package that has been developed for the analysis of time series using linear Gaussian state space models (SSM).

PySSM is easy to use; models can be set up quickly and efficiently and a variety of different settings are available to the user. It also takes advantage of scientific libraries Numpy and Scipy and other high level features of the Python language.

PySSM default is also used as a platform for interfacing between optimised and parallelised FORTRAN routines. These FORTRAN routines heavily utilise Basic Linear Algebra (BLAS) and Linear Algebra Package (LAPACK) functions for maximum performance.

PySSM contains classes for filtering, classical smoothing as well as simulation smoothing.

You can access the code from the git repository and submit bugs/requests viat the issue tracker.