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This repository houses the source and Python scripts producing the paper"Estimating time series models by state space methods in Python: Statsmodels".

A PDF version of the paper can be found in the repository, and also at:https://github.com/ChadFulton/fulton_statsmodels_2017/raw/master/fulton_statsmodels_2017_v1.pdf

There are three Jupyter notebooks with code showing maximum likelihood andBayesian estimation of three example models:

• ARMA(1, 1) model
• Local level model
• Simple Real Business Cycle model

The paper is written usingSphinx. Inparticular, see:

• paper/source for the reStructuredText files of text
• paper/source/sections/code for all of the code that is referenced in thetext and that produces the output and figures. To run all code and produceall output, runpython run_all.py in that directory.
• notebooks for Jupyter notebooks that flesh out the three examples in thepaper (ARMA(1, 1), local level, and a simple real business cycle model)

To build the paper, in a terminal from the base directory, you must:

>>>cd paper/source/sections/code>>> python run_all.py>>>cd ../../../>>> make html>>> make latex