bib.bib

@article{donegan_2021,
  title={Spatial conditional autoregressive models in Stan},
  author={Donegan, Connor},
  year={2021},
  journal={OSF Preprints},
  doi={https://doi.org/10.31219/osf.io/3ey65}
}

@article{riebler_2016,
  title={An intuitive Bayesian spatial model for disease mapping that accounts for scaling},
  author={Riebler, Andrea and S{\o}rbye, Sigrunn H and Simpson, Daniel and Rue, H{\aa}vard},
  journal={Statistical Methods in Medical Research},
  volume={25},
  number={4},
  pages={1145--1165},
  year={2016}
}

@article{morris_2019,
  title={Bayesian hierarchical spatial models: Implementing the Besag York Molli{\'e} model in stan},
  author={Morris, Mitzi and Wheeler-Martin, Katherine and Simpson, Dan and Mooney, Stephen J and Gelman, Andrew and DiMaggio, Charles},
  journal={Spatial and Spatio-temporal Epidemiology},
  volume={31},
  pages={100301},
  year={2019}
}

@article{besag_1991,
  title={Bayesian image restoration, with two applications in spatial statistics},
  author={Besag, Julian and York, Jeremy and Molli{\'e}, Annie},
  journal={Annals of the Institute of Statistical Mathematics},
  volume={43},
  number={1},
  pages={1--20},
  year={1991}
}

@book{haining_2020,
  title={Modelling Spatial and Spatio-Temporal Data: A Bayesian Approach},
  author={Haining, Robert and Li, Guangquan},
  publisher={CRC Press},
  year=2020
}

@article{freni_2018,
  title={A note on intrinsic conditional autoregressive models for disconnected graphs},
  author={Freni-Sterrantino, Anna and Ventrucci, Massimo and Rue, H{\aa}vard},
  journal={Spatial and Spatio-temporal Epidemiology},
  volume={26},
  pages={25-34},
  year={2018}
}

@book{rue_2005,
  title={Gaussian Markov random fields: theory and applications},
  author={Rue, Havard and Held, Leonhard},
  year={2005},
  publisher={CRC press}
}