Deploying to gh-pages from @ 03a6932 🚀

Author: VisruthSK

dev/CONTRIBUTING.html

@@ -0,0 +1,73 @@
+# Contributing to loo
+
+This outlines how to propose a change to loo and is based on similar
+instructions for tidyverse packages, including the contributing
+guidelines generated by `usethis::use_tidy_contributing()`.
+
+## Fixing typos
+
+You can fix typos, spelling mistakes, or grammatical errors in the
+documentation directly using the GitHub web interface, as long as the
+changes are made in the *source* file. This generally means you’ll need
+to edit [roxygen2
+comments](https://roxygen2.r-lib.org/articles/roxygen2.html) in an `.R`,
+not a `.Rd` file. You can find the `.R` file that generates the `.Rd` by
+reading the comment in the first line.
+
+## Bigger changes
+
+If you want to make a bigger change, it’s a good idea to first file an
+issue and make sure someone from the team agrees that it’s needed. If
+you’ve found a bug, please file an issue that illustrates the bug with a
+minimal reproducible example (see e.g. the [tidyverse reprex
+instructions](https://www.tidyverse.org/help/#reprex)). The tidyverse
+guide on [how to create a great
+issue](https://code-review.tidyverse.org/issues/) has more advice.
+
+### Pull request process
+
+If you are new to creating pull requests here are some tips. Using the
+functions from the `usethis` package is not required but can be helpful
+if this process is new to you.
+
+- Fork the package and clone onto your computer. If you haven’t done
+  this before, we recommend using
+  `usethis::create_from_github("stan-dev/loo", fork = TRUE)`.
+
+- Install all development dependencies with
+  `devtools::install_dev_deps()`, and then make sure the package passes
+  R CMD check by running `devtools::check()`. If R CMD check doesn’t
+  pass cleanly, it’s a good idea to ask for help before continuing.
+
+- Create a Git branch for your pull request (PR). We recommend using
+  `usethis::pr_init("brief-description-of-change")`.
+
+- Make your changes, commit to git, and then create a PR by running
+  `usethis::pr_push()`, and following the prompts in your browser. The
+  title of your PR should briefly describe the change. The body of your
+  PR should contain `Fixes #issue-number`.
+
+- For user-facing changes, add a bullet to the top of `NEWS.md`
+  (i.e. just below the first header). Follow the style already used in
+  `NEWS.md`.
+
+### Code style
+
+- New code should attempt to follow the style used in the package. When
+  in doubt follow the tidyverse [style
+  guide](https://style.tidyverse.org).
+
+- We use [roxygen2](https://cran.r-project.org/package=roxygen2), with
+  [Markdown
+  syntax](https://cran.r-project.org/web/packages/roxygen2/vignettes/rd-formatting.html),
+  for documentation.
+
+- We use [testthat](https://cran.r-project.org/package=testthat) for
+  unit tests. Contributions with test cases included are easier to
+  accept.
+
+## Code of Conduct
+
+Please note that the loo project follows the Stan project’s [Code of
+Conduct](https://discourse.mc-stan.org/t/announcing-our-new-stan-code-of-conduct/23764).
+By contributing to this project you agree to abide by its terms.

dev/CONTRIBUTING.md

@@ -0,0 +1,42 @@
+# Articles
+
+### Getting started
+
+These vignettes demonstrate how to use the **loo** package to perform
+approximate leave-one-out cross-validation or exact K-fold
+cross-validation for Bayesian models fit using MCMC, compare models on
+estimated predictive performance on new data, and weight models for
+averaging predictive distributions.
+
+- [Using the loo package (version \>=
+  2.0.0)](https://mc-stan.org/loo/dev/articles/loo2-example.md):
+- [Bayesian Stacking and Pseudo-BMA weights using the loo
+  package](https://mc-stan.org/loo/dev/articles/loo2-weights.md):
+- [Writing Stan programs for use with the loo
+  package](https://mc-stan.org/loo/dev/articles/loo2-with-rstan.md):
+- [Holdout validation and K-fold cross-validation of Stan programs with
+  the loo package](https://mc-stan.org/loo/dev/articles/loo2-elpd.md):
+
+### Additional topics
+
+These vignettes demonstrate how to use the **loo** package for more
+complicated scenarios including models with non-factorized likelihoods,
+forecasting models, models fit to very large datasets, and more.
+
+- [Leave-one-out cross-validation for non-factorized
+  models](https://mc-stan.org/loo/dev/articles/loo2-non-factorized.md):
+- [Approximate leave-future-out cross-validation for Bayesian time
+  series models](https://mc-stan.org/loo/dev/articles/loo2-lfo.md):
+- [Using Leave-one-out cross-validation for large
+  data](https://mc-stan.org/loo/dev/articles/loo2-large-data.md):
+- [Avoiding model refits in leave-one-out cross-validation with moment
+  matching](https://mc-stan.org/loo/dev/articles/loo2-moment-matching.md):
+- [Mixture IS leave-one-out cross-validation for high-dimensional
+  Bayesian models](https://mc-stan.org/loo/dev/articles/loo2-mixis.md):
+
+### Frequently asked questions
+
+- [Cross-validation FAQ](https://users.aalto.fi/~ave/CV-FAQ.html):
+
+  Answers to frequently asked questions about cross-validation and the
+  **loo** package (links to external site).