Update glm robust with outliers and add extra dependency template

.github/PULL_REQUEST_TEMPLATE.md

@@ -8,7 +8,7 @@ Please let us know if the reviews are unclear or the recommended next step seems
 if you would like help in addressing a reviewer's comments,
 or if you have been waiting too long to hear back on your PR. -->
 
-+ [ ] Notebook follows style guide https://github.com/pymc-devs/pymc/wiki/PyMC-Jupyter-Notebook-Style-Guide
++ [ ] Notebook follows style guide https://docs.pymc.io/en/latest/contributing/jupyter_style.html
 + [ ] PR description contains a link to the relevant issue: a tracker one for existing notebooks or a proposal one for new notebooks
 
 

CONTRIBUTING.md

@@ -27,10 +27,13 @@ Therefore, all notebooks will be progressively updated along this path:
 
 ```
          / --> General updates -- \
-To Do --<                          >--> Best Practices (--> v4)
+To Do --<                          >--> Best Practices --> v4
          \ -->      ArviZ      -- /
 ```
 
+See https://github.com/pymc-devs/pymc-examples/wiki/Notebook-updates-overview for a more detailed
+description of what each of the status mean.
+
 Each pull request should update a single notebook 1-2 positions to the right.
 Before starting a work on a pull request look at the tracker issue of the
 notebook you are planning to edit to make sure it is not being updated by someone

examples/conf.py

@@ -31,6 +31,8 @@
     ".DS_Store",
     "*import_posts*",
     "**/.ipynb_checkpoints/*",
+    "extra_installs.md",
+    "page_footer.md",
 ]
 
 
@@ -104,13 +106,22 @@
 blog_baseurl = "https://examples.pymc.io"
 blog_title = "PyMC Examples"
 blog_path = "blog"
+blog_authors = {
+    "contributors": ("PyMC Contributors", "https://docs.pymc.io"),
+}
+blog_default_author = "contributors"
 fontawesome_included = True
 # post_redirect_refresh = 1
 # post_auto_image = 1
 # post_auto_excerpt = 2
 
 # MyST config
 myst_enable_extensions = ["colon_fence", "deflist", "dollarmath", "amsmath", "substitution"]
+myst_substitutions = {
+    "pip_dependencies": "{{ extra_dependencies }}",
+    "conda_dependencies": "{{ extra_dependencies }}",
+    "extra_install_notes": "",
+}
 jupyter_execute_notebooks = "off"
 
 # bibtex config

examples/extra_installs.md

@@ -0,0 +1,38 @@
+:::{attention}
+This notebook uses libraries that are not PyMC dependencies
+and therefore need to be installed specifically to run this notebook.
+Open the dropdown below for extra guidance.
+:::
+
+::::::{dropdown} Extra dependencies install instructions
+:icon: package-dependencies
+In order to run this notebook (either locally or on binder) you won't only
+need a working PyMC installation with all optional dependencies,
+but also to install some extra dependencies.
+For advise on installing PyMC itself, please refer to {ref}`pymc:installation`
+
+You can install these dependencies with your preferred package manager, we provide
+as an example the pip and conda commands below.
+
+> $ pip install {{ pip_dependencies }}
+
+Note that if you want (or need) to install the packages from inside the notebook instead
+of the command line, you can install
+the packages by running a variation of the pip command:
+
+> import sys
+>
+> !{sys.executable} -m pip install {{ pip_dependencies }}
+
+You should not run `!pip install` as it might install the package in a different
+environment and not be available from the Jupyter notebook even if installed.
+
+Another alternative is using conda instead:
+
+> $ conda install {{ conda_dependencies }}
+
+when installing scientific python packages with conda,
+we recommend using [conda forge](https://conda-forge.org/index.html)
+
+{{ extra_install_notes }}
+::::::

examples/generalized_linear_models/GLM-robust.ipynb

@@ -468,7 +468,7 @@
  "metadata": {
   "anaconda-cloud": {},
   "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "Python 3 (ipykernel)",
    "language": "python",
    "name": "python3"
   },
@@ -482,7 +482,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.10"
+   "version": "3.9.7"
   },
   "latex_envs": {
    "bibliofile": "biblio.bib",

examples/getting_started.ipynb

@@ -41,10 +41,9 @@
    "source": [
     "## Installation\n",
     "\n",
-    "----\n",
-    "**Note:** These instructions are out of date, and no longer correct. Please see the [Installation instructions](https://github.com/pymc-devs/pymc3#Installation) on the [GitHub site for PyMC3](https://github.com/pymc-devs/pymc3).\n",
-    "\n",
-    "----\n",
+    ":::{caution}\n",
+    "These instructions are out of date, and no longer correct. Please see the [Installation instructions](https://github.com/pymc-devs/pymc3#Installation) on the [GitHub site for PyMC3](https://github.com/pymc-devs/pymc3).\n",
+    ":::\n",
     "\n",
     "Running PyMC3 requires a working Python interpreter, either version 2.7 (or more recent) or 3.5 (or more recent); we recommend that new users install version 3.5. A complete Python installation for Mac OSX, Linux and Windows can most easily be obtained by downloading and installing the free [`Anaconda Python Distribution`](https://store.continuum.io/cshop/anaconda/) by ContinuumIO. \n",
     "\n",

examples/references.bib

@@ -1,3 +1,21 @@
+@misc{carpenter2016hierarchical,
+  title={Hierarchical partial pooling for repeated binary trials},
+  author={Carpenter, Bob and Gabry, J and Goodrich, B},
+  year={2016},
+  publisher={Technical report. Retrieved from https://mc-stan. org/users/docum entat ion~…}
+}
+
+@article{efron1975data,
+  title={Data analysis using Stein's estimator and its generalizations},
+  author={Efron, Bradley and Morris, Carl},
+  journal={Journal of the American Statistical Association},
+  volume={70},
+  number={350},
+  pages={311--319},
+  year={1975},
+  publisher={Taylor \& Francis}
+}
+
 @book{gelman2006data,
   title={Data analysis using regression and multilevel/hierarchical models},
   author={Gelman, Andrew and Hill, Jennifer},
@@ -16,6 +34,25 @@ @article{gelman2006multilevel
   publisher={Taylor \& Francis}
 }
 
+@article{gelman2008scaling,
+  title={Scaling regression inputs by dividing by two standard deviations},
+  author={Gelman, Andrew},
+  journal={Statistics in medicine},
+  volume={27},
+  number={15},
+  pages={2865--2873},
+  year={2008},
+  publisher={Wiley Online Library},
+  doi={10.1002/sim.3107}
+}
+
+@book{gelman2013bayesian,
+  title={Bayesian Data Analysis},
+  publisher={Chapman and Hall/CRC},
+  author={Gelman, Andrew and Carlin, John B. and Stern, Hal S. and Dunson, David B. and Vehtari, Aki and Rubin, Donald B.},
+  year={2013}
+}
+
 @article{goldberg2001eigentaste,
     author = {Ken Goldberg and Theresa Roeder and Chris Perkins},
     title = {Eigentaste: A Constant Time Collaborative Filtering Algorithm},
@@ -37,19 +74,47 @@ @misc{harper2015movielens
   url={https://doi.org/10.1145/2827872}
 }
 
-@article{koren2009matrixfactorization,  
-author={Koren, Yehuda and Bell, Robert and Volinsky, Chris},  
-  journal={Computer},   
-  title={Matrix Factorization Techniques for Recommender Systems},   
-  year={2009},  
-  volume={42},  
-  number={8},  
-  pages={30--37},  
+@misc{hogg2010data,
+      title={Data analysis recipes: Fitting a model to data},
+      author={David W. Hogg and Jo Bovy and Dustin Lang},
+      year={2010},
+      eprint={1008.4686},
+      archivePrefix={arXiv},
+      primaryClass={astro-ph.IM}
+}
+
+@book{ivezić2014astroMLtext,
+  author = {Željko Ivezić and Andrew J. Connolly and Jacob T. VanderPlas and Alexander Gray},
+  doi = {10.1515/9781400848911},
+  title = {Statistics, Data Mining, and Machine Learning in Astronomy: A Practical Python Guide for the Analysis of Survey Data},
+  year = {2014},
+  publisher = {Princeton University Press},
+  ISBN = {9781400848911}
+}
+
+@book{james2021statisticallearning,
+  title={An Introduction to Statistical Learning},
+  author={James, Gareth ad Witten, Daniela and Hastie, Trevor and Tibshirani, Robert},
+  year={2021},
+  publisher={Springer},
+  doi={https://doi.org/10.1007/978-1-0716-1418-1},
+  issn={1431-875X},
+  isbn={978-1-0716-1420-4}
+}
+
+@article{koren2009matrixfactorization,
+author={Koren, Yehuda and Bell, Robert and Volinsky, Chris},
+  journal={Computer},
+  title={Matrix Factorization Techniques for Recommender Systems},
+  year={2009},
+  volume={42},
+  number={8},
+  pages={30--37},
   doi={10.1109/MC.2009.263}
 }
 
 @misc{kingma2014autoencoding,
-  title={Auto-Encoding Variational Bayes}, 
+  title={Auto-Encoding Variational Bayes},
   author={Diederik P Kingma and Max Welling},
   year={2014},
   eprint={1312.6114},
@@ -58,61 +123,14 @@ @misc{kingma2014autoencoding
 }
 
 @misc{kucukelbir2015automatic,
-  title={Automatic Variational Inference in Stan}, 
+  title={Automatic Variational Inference in Stan},
   author={Alp Kucukelbir and Rajesh Ranganath and Andrew Gelman and David M. Blei},
   year={2015},
   eprint={1506.03431},
   archivePrefix={arXiv},
   primaryClass={stat.ML}
 }
 
-@book{mcelreath2018statistical,
-  title={Statistical rethinking: A Bayesian course with examples in R and Stan},
-  author={McElreath, Richard},
-  year={2018},
-  publisher={Chapman and Hall/CRC}
-}
-
-@misc{mnih2013playing,
-  title={Playing Atari with Deep Reinforcement Learning}, 
-  author={Volodymyr Mnih and Koray Kavukcuoglu and David Silver and Alex Graves and Ioannis Antonoglou and Daan Wierstra and Martin Riedmiller},
-  year={2013},
-  eprint={1312.5602},
-  archivePrefix={arXiv},
-  primaryClass={cs.LG}
-}
-
-@article{silver2016masteringgo,
-  title={Mastering the game of Go with deep neural networks and tree search},
-  author={D. Silver, A. Huang, C. Maddison et al.},
-  journal={Nature},
-  volume={529},
-  pages={484--489},
-  year={2016},
-  url={https://doi.org/10.1038/nature16961}
-}
-
-@book{james2021statisticallearning,
-  title={An Introduction to Statistical Learning},
-  author={James, Gareth ad Witten, Daniela and Hastie, Trevor and Tibshirani, Robert},
-  year={2021},
-  publisher={Springer},
-  doi={https://doi.org/10.1007/978-1-0716-1418-1},
-  issn={1431-875X},
-  isbn={978-1-0716-1420-4}
-}
-
-@book{wilkinson2005grammar,
-  title={The Grammar of Graphics},
-  author={Wilkinson, Leland},
-  year={2005},
-  publisher={Springer},
-  doi={https://doi.org/10.1007/0-387-28695-0},
-  issn={1431-8784},
-  isbn={978-0-387-24544-7}
-}
-
-
 @article{lewandowski2009generating,
   title={Generating random correlation matrices based on vines and extended onion method},
   author={Lewandowski, Daniel and Kurowicka, Dorota and Joe, Harry},
@@ -124,6 +142,13 @@ @article{lewandowski2009generating
   publisher={Elsevier}
 }
 
+@book{mcelreath2018statistical,
+  title={Statistical rethinking: A Bayesian course with examples in R and Stan},
+  author={McElreath, Richard},
+  year={2018},
+  publisher={Chapman and Hall/CRC}
+}
+
 @inproceedings{mnih2008advances,
   title={Probabilistic Matrix Factorization},
   author={Mnih, Andriy and Salakhutdinov, Russ R},
@@ -135,6 +160,15 @@ @inproceedings{mnih2008advances
   year={2008}
 }
 
+@misc{mnih2013playing,
+  title={Playing Atari with Deep Reinforcement Learning},
+  author={Volodymyr Mnih and Koray Kavukcuoglu and David Silver and Alex Graves and Ioannis Antonoglou and Daan Wierstra and Martin Riedmiller},
+  year={2013},
+  eprint={1312.5602},
+  archivePrefix={arXiv},
+  primaryClass={cs.LG}
+}
+
 @article{nowlan1992simplifying,
   title={Simplifying Neural Networks By Soft Weight-Sharing},
   author={Nowlan, Steven J and Hinton, Geoffrey E},
@@ -146,6 +180,7 @@ @article{nowlan1992simplifying
   publisher={MIT Press}
 }
 
+
 @inproceedings{salakhutdinov2008bayesian,
   title={Bayesian Probabilistic Matrix Factorization Using Markov Chain Monte Carlo},
   author={Salakhutdinov, Ruslan and Mnih, Andriy},
@@ -155,35 +190,43 @@ @inproceedings{salakhutdinov2008bayesian
   volume={25}
 }
 
+@article{silver2016masteringgo,
+  title={Mastering the game of Go with deep neural networks and tree search},
+  author={D. Silver, A. Huang, C. Maddison et al.},
+  journal={Nature},
+  volume={529},
+  pages={484--489},
+  year={2016},
+  url={https://doi.org/10.1038/nature16961}
+}
+
 @misc{szegedy2014going,
-  title={Going Deeper with Convolutions}, 
+  title={Going Deeper with Convolutions},
   author={Christian Szegedy and Wei Liu and Yangqing Jia and Pierre Sermanet and Scott Reed and Dragomir Anguelov and Dumitru Erhan and Vincent Vanhoucke and Andrew Rabinovich},
   year={2014},
   eprint={1409.4842},
   archivePrefix={arXiv},
   primaryClass={cs.CV}
   }
-
-@misc{carpenter2016hierarchical,
-  title={Hierarchical partial pooling for repeated binary trials},
-  author={Carpenter, Bob and Gabry, J and Goodrich, B},
-  year={2016},
-  publisher={Technical report. Retrieved from https://mc-stan. org/users/docum entat ion~…}
-}
 
-@book{gelman2013bayesian, 
-  title={Bayesian Data Analysis},
-  publisher={Chapman and Hall/CRC}, 
-  author={Gelman, Andrew and Carlin, John B. and Stern, Hal S. and Dunson, David B. and Vehtari, Aki and Rubin, Donald B.},
-  year={2013}
+
+@INPROCEEDINGS{vanderplas2012astroML,
+ author={{Vanderplas}, J.T. and {Connolly}, A.J.
+         and {Ivezi{\'c}}, {\v Z}. and {Gray}, A.},
+ booktitle={Conference on Intelligent Data Understanding (CIDU)},
+ title={Introduction to astroML: Machine learning for astrophysics},
+ month={oct.},
+ pages={47 -54},
+ doi={10.1109/CIDU.2012.6382200},
+ year={2012}
 }
-@article{efron1975data,
-  title={Data analysis using Stein's estimator and its generalizations},
-  author={Efron, Bradley and Morris, Carl},
-  journal={Journal of the American Statistical Association},
-  volume={70},
-  number={350},
-  pages={311--319},
-  year={1975},
-  publisher={Taylor \& Francis}
+
+@book{wilkinson2005grammar,
+  title={The Grammar of Graphics},
+  author={Wilkinson, Leland},
+  year={2005},
+  publisher={Springer},
+  doi={https://doi.org/10.1007/0-387-28695-0},
+  issn={1431-8784},
+  isbn={978-0-387-24544-7}
 }