update truncated/censored notebook to v4 (#271)

* create truncated regression example

* delete truncated regression example from main branch

* update censored model to v4 using pm.Censored

* comply with style guide, hopefully

* addressing pull request comments

* markdown edits

* perfecting wording around the censored distribution plot

* fix citations and cross-references

Co-authored-by: Benjamin T. Vincent <[email protected]>
Co-authored-by: Oriol (ZBook) <[email protected]>

Author: 3 people

examples/generalized_linear_models/GLM-truncated-censored-regression.ipynb

@@ -1,3 +1,23 @@
+@article{ando2007bayesian,
+  title={Bayesian predictive information criterion for the evaluation of hierarchical Bayesian and empirical Bayes models},
+  author={Ando, Tomohiro},
+  journal={Biometrika},
+  volume={94},
+  number={2},
+  pages={443--458},
+  year={2007},
+  publisher={Oxford University Press},
+  doi={10.1093/biomet/asm017}
+}
+
+@book{breen1996regression,
+  title={Regression models: Censored, sample selected, or truncated data},
+  author={Breen, Richard and others},
+  volume={111},
+  year={1996},
+  publisher={Sage}
+}
+
 @misc{carpenter2016hierarchical,
   title={Hierarchical partial pooling for repeated binary trials},
   author={Carpenter, Bob and Gabry, J and Goodrich, B},
@@ -53,6 +73,13 @@ @book{gelman2013bayesian
   year={2013}
 }
 
+@book{gelman2020regression,
+  title={Regression and other stories},
+  author={Gelman, Andrew and Hill, Jennifer and Vehtari, Aki},
+  year={2020},
+  publisher={Cambridge University Press}
+}
+
 @article{goldberg2001eigentaste,
     author = {Ken Goldberg and Theresa Roeder and Chris Perkins},
     title = {Eigentaste: A Constant Time Collaborative Filtering Algorithm},
@@ -62,6 +89,20 @@ @article{goldberg2001eigentaste
     pages = {133--151}
 }
 
+@article{goodman1999,
+  doi = {10.7326/0003-4819-130-12-199906150-00008},
+  url = {https://doi.org/10.7326/0003-4819-130-12-199906150-00008},
+  year = {1999},
+  month = jun,
+  publisher = {American College of Physicians},
+  volume = {130},
+  number = {12},
+  pages = {995},
+  author = {Steven N. Goodman},
+  title = {Toward Evidence-Based Medical Statistics. 1: The P Value Fallacy},
+  journal = {Annals of Internal Medicine}
+}
+
 @misc{harper2015movielens,
   title={The MovieLens Datasets: History and Context},
   author={Harper, F. Maxwell and Konstan, Joseph A.},
@@ -102,8 +143,22 @@ @book{james2021statisticallearning
   isbn={978-1-0716-1420-4}
 }
 
+@article{johnson1999,
+  doi = {10.2307/3802789},
+  url = {https://doi.org/10.2307/3802789},
+  year = {1999},
+  month = jul,
+  publisher = {{JSTOR}},
+  volume = {63},
+  number = {3},
+  pages = {763},
+  author = {Douglas H. Johnson},
+  title = {The Insignificance of Statistical Significance Testing},
+  journal = {The Journal of Wildlife Management}
+}
+
 @article{koren2009matrixfactorization,
-author={Koren, Yehuda and Bell, Robert and Volinsky, Chris},
+  author={Koren, Yehuda and Bell, Robert and Volinsky, Chris},
   journal={Computer},
   title={Matrix Factorization Techniques for Recommender Systems},
   year={2009},
@@ -122,6 +177,19 @@ @misc{kingma2014autoencoding
   primaryClass={stat.ML}
 }
 
+@article{kruschke2013,
+  doi = {10.1037/a0029146},
+  url = {https://doi.org/10.1037/a0029146},
+  year = {2013},
+  publisher = {American Psychological Association ({APA})},
+  volume = {142},
+  number = {2},
+  pages = {573--603},
+  author = {John K. Kruschke},
+  title = {Bayesian estimation supersedes the t test.},
+  journal = {Journal of Experimental Psychology: General}
+}
+
 @misc{kucukelbir2015automatic,
   title={Automatic Variational Inference in Stan},
   author={Alp Kucukelbir and Rajesh Ranganath and Andrew Gelman and David M. Blei},
@@ -219,14 +287,14 @@ @misc{szegedy2014going
 
 
 @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}
+  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}
 }
 
 @book{wilkinson2005grammar,
@@ -239,43 +307,4 @@ @book{wilkinson2005grammar
   isbn={978-0-387-24544-7}
 }
 
-@article{kruschke2013,
-  doi = {10.1037/a0029146},
-  url = {https://doi.org/10.1037/a0029146},
-  year = {2013},
-  publisher = {American Psychological Association ({APA})},
-  volume = {142},
-  number = {2},
-  pages = {573--603},
-  author = {John K. Kruschke},
-  title = {Bayesian estimation supersedes the t test.},
-  journal = {Journal of Experimental Psychology: General}
-}
 
-@article{goodman1999,
-  doi = {10.7326/0003-4819-130-12-199906150-00008},
-  url = {https://doi.org/10.7326/0003-4819-130-12-199906150-00008},
-  year = {1999},
-  month = jun,
-  publisher = {American College of Physicians},
-  volume = {130},
-  number = {12},
-  pages = {995},
-  author = {Steven N. Goodman},
-  title = {Toward Evidence-Based Medical Statistics. 1: The P Value Fallacy},
-  journal = {Annals of Internal Medicine}
-}
-
-@article{johnson1999,
-  doi = {10.2307/3802789},
-  url = {https://doi.org/10.2307/3802789},
-  year = {1999},
-  month = jul,
-  publisher = {{JSTOR}},
-  volume = {63},
-  number = {3},
-  pages = {763},
-  author = {Douglas H. Johnson},
-  title = {The Insignificance of Statistical Significance Testing},
-  journal = {The Journal of Wildlife Management}
-}

examples/references.bib

@@ -4,6 +4,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
+    "(censored_data)=\n",
     "# Censored Data Models"
    ]
   },
@@ -369,6 +370,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
+    "(censored_data/model1)=\n",
     "### Model 1 - Imputed Censored Model of Censored Data\n",
     "\n",
     "In this model, we impute the censored values from the same distribution as the uncensored data. Sampling from the posterior generates possible uncensored data sets.\n",
@@ -676,7 +678,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "Python 3 (ipykernel)",
    "language": "python",
    "name": "python3"
   },
@@ -690,7 +692,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.5"
+   "version": "3.9.7"
   }
  },
  "nbformat": 4,