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Fixed typos and did some cleaning
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avehtari authored Oct 12, 2023
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Posterior keywords
==================

Below are the definition of some of the keywords used. These are tags added to posterior that we __known__. Hence, there might exist posteriors that should have the keyword where it is currently missing. If you see this, please file an issue and we will try to fix it.
Below are the definition of some of the keywords used. These are tags added to posterior that we __know__. Hence, there might exist posteriors that should have the keyword where it is currently missing. If you see this, please file an issue and we will fix it.

```easy```: Posteriors that can be computed with standard Stan settings (adapt delta = 0.8) without any divergent transitions for 10 000 draws and on average uses less than 100 leapfrog steps.
```easy```: Posteriors that can be computed with standard Stan settings (adapt delta = 0.8) without any divergent transitions for 10 000 draws and on average use less than 100 leapfrog steps per iteration.

```slow```: Posteriors that takes more than 1h to run 1000 iterations/warmup on a standard CPU. The difficulties can be due to different reasons.
```slow```: Posteriors that take more than 1h to run 1000 iterations/warmup on a standard CPU. The difficulties can be due to different reasons.

```arm book```: Posteriors that can be found in "Gelman, A., & Hill, J. (2006). Data analysis using regression and multilevel/hierarchical models. Cambridge University Press."

```arm book```: Posteriors that can be found in Gelman, A., & Hill, J. (2006). Data analysis using regression and multilevel/hierarchical models. Cambridge university press.
```pathfinder paper```: Posteriors used in "Zhang, L., Carpenter, B., Gelman, A., & Vehtari, A. (2022). Pathfinder: Parallel quasi-Newton variational inference. Journal of Machine Learning Research, 23(306), 1-49."

```pathfinder paper```: Posteriors used in Zhang, L., Carpenter, B., Gelman, A., & Vehtari, A. (2022). Pathfinder: Parallel quasi-Newton variational inference. Journal of Machine Learning Research, 23(306), 1-49.
```bpa book```: Posteriors translated by Hiroki Itô from "Kéry, M., & Schaub, M. (2011). Bayesian population analysis using WinBUGS: a hierarchical perspective. Academic Press."

```bpa book```: Posteriors translated by Hiroki Itô from Kéry, M., & Schaub, M. (2011). Bayesian population analysis using WinBUGS: a hierarchical perspective. Academic Press.
```stan benchmark```: Posteriors used in the Stan repository "Benchmark Models for Evaluating Algorithm Accuracy. https://github.com/stan-dev/stat_comp_benchmarks".

```stan benchmark```: Early posteriors used in the Stan repository "Benchmark Models for Evaluating Algorithm Accuracy". The repository can be found here:
https://github.com/stan-dev/stat_comp_benchmarks
```stan case study```: Posteriors from "Stan cases studies. https://mc-stan.org/users/documentation/case-studies.html".

```stan case study```: Posteriors for Stan cases studies. See the following URL for more information:
https://mc-stan.org/users/documentation/case-studies.html
```warmup paper```: Posteriors used in "Bales, B., Pourzanjani, A., Vehtari, A., & Petzold, L. (2019). Selecting the metric in Hamiltonian monte carlo. arXiv preprint arXiv:1905.11916."

```warmup paper```: Posteriors used in Bales, B., Pourzanjani, A., Vehtari, A., & Petzold, L. (2019). Selecting the metric in Hamiltonian monte carlo. arXiv preprint arXiv:1905.11916.
```bugs examples``` Posteriors from "BUGS example models and data. https://github.com/stan-dev/example-models/tree/master/bugs_examples".

```bugs examples``` Posteriors from BUGS example models and data. See the following URL for more information: https://github.com/stan-dev/example-models/tree/master/bugs_examples

```stan examples``` Posteriors from Stan examples at: https://github.com/stan-dev/example-models
```stan examples``` Posteriors from "Stan examples. https://github.com/stan-dev/example-models".

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