This page collects files and computer code for the paper Goodness of Fit for Markov Models: A Density Approach by Vance Martin, Yoshihiko Nishiyama and John Stachurski.

We propose a density-based goodness of fit test suitable for time series data. The test compares the data against a parametric class of models specified in the null hypothesis. Estimation of smoothing parameters is not required, and the test has nontrivial power against $1/\sqrt{n}$ local alternatives.

Implementations are provided in both Python and C. The Python code is more straightforward and portable, but the C code is significantly faster.