add citation

Author: aloctavodia

README.md

@@ -11,6 +11,22 @@ Additional information can be found in the [Contributing Readme](https://github.
 pymc_bart wishes to maintain a positive community. Additional details
 can be found in the [Code of Conduct](https://github.com/pymc-devs/pymc_bart/blob/main/CODE_OF_CONDUCT.md)
 
+## Citation
+If you use PyMC-BART and want to cite it please use [![arXiv](https://img.shields.io/badge/arXiv-2206.03619-b31b1b.svg)](https://arxiv.org/abs/2206.03619)
+
+Here is the citation in BibTeX format
+
+@misc{quiroga2022bart,
+  doi = {10.48550/ARXIV.2206.03619},
+  url = {https://arxiv.org/abs/2206.03619},
+  author = {Quiroga, Miriana and Garay, Pablo G and Alonso, Juan M. and Loyola, Juan Martin and Martin, Osvaldo A},
+  keywords = {Computation (stat.CO), FOS: Computer and information sciences, FOS: Computer and information sciences},
+  title = {Bayesian additive regression trees for probabilistic programming},
+  publisher = {arXiv},
+  year = {2022},
+  copyright = {Creative Commons Attribution Share Alike 4.0 International}
+}
+
 ## Donations
 pymc_bart, as other pymc-devs projects, is a non-profit project under the NumFOCUS umbrella. If you want to support pymc_bart financially, you can donate [here](https://numfocus.org/donate-to-pymc).
 

docs/index.rst

@@ -21,7 +21,7 @@ Bayesian Additive Regression Trees for Probabilistic programming with PyMC
 
 Dependencies
 ============
-PyM-BART is tested on Python 3.8+ and depends on PyMC V4.
+PyMC-BART is tested on Python 3.8+ and depends on PyMC V4.
 
 Installation
 ============
@@ -30,6 +30,31 @@ Installation
 
   pip install git+https://github.com/pymc-devs/pymc-bart.git
 
+
+Citation
+========
+If you use Bambi and want to cite it please use |arXiv|
+
+.. |arXiv| image:: https://img.shields.io/badge/arXiv-2206.03619-b31b1b.svg
+    :target: https://arxiv.org/abs/2206.03619
+
+Here is the citation in BibTeX format
+
+.. code-block::
+
+    @misc{quiroga2022bart,
+      doi = {10.48550/ARXIV.2206.03619},
+      url = {https://arxiv.org/abs/2206.03619},
+      author = {Quiroga, Miriana and Garay, Pablo G and Alonso, Juan M. and Loyola, Juan Martin and Martin, Osvaldo A},
+      keywords = {Computation (stat.CO), FOS: Computer and information sciences, FOS: Computer and information sciences},
+      title = {Bayesian additive regression trees for probabilistic programming},
+      publisher = {arXiv},
+      year = {2022},
+      copyright = {Creative Commons Attribution Share Alike 4.0 International}
+    }
+
+
+
 Contributing
 ============
 We welcome contributions from interested individuals or groups! For information about contributing to PyMC-BART check out our instructions, policies, and guidelines `here <https://github.com/pymc-devs/pymc-bart/blob/main/CONTRIBUTING.md>`_.