This repository contains a Jupyter notebook demonstrating the use of Gibbs sampling to performing interpolation of missing data described by an autoregressive model. This is based on Chapter 6 of Numerical Bayesian Methods Applied to Signal Processing by J. Ó Ruanaidh & W. Fitzgerald.

The notebook can be run in a conda environment generated using the provided environment.yml file. E.g., Create and activate the environment with:

conda env create -f environment.yml
conda activate interp-autoreg

then set up the extension to enable equation numbering (just do this once):

jupyter contrib nbextension install --user
jupyter nbextension enable equation-numbering/main

and open the notebook with:

jupyter notebook interp-autoreg.ipynb &