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(2017). Practical Bayesian model \nevaluation using leave-one-out cross-validation and WAIC. \n_Statistics and Computing_. 27(5), 1413--1432. \ndoi:10.1007/s11222-016-9696-4. [Online](https://link.springer.com/article/10.1007/s11222-016-9696-4), \n[arXiv preprint arXiv:1507.04544](https://arxiv.org/abs/1507.04544).\n\nand computes model weights as described in\n\n* Yao, Y., Vehtari, A., Simpson, D., and Gelman, A. (2018). Using\nstacking to average Bayesian predictive distributions. In Bayesian\nAnalysis, doi:10.1214/17-BA1091. \n[Online](https://projecteuclid.org/euclid.ba/1516093227),\n[arXiv preprint arXiv:1704.02030](https://arxiv.org/abs/1704.02030).\n\nFrom existing posterior simulation draws, we compute approximate LOO-CV using\nPareto smoothed importance sampling (PSIS), a new procedure for regularizing\nimportance weights. As a byproduct of our calculations, we also obtain\napproximate standard errors for estimated predictive errors and for comparing\npredictive errors between two models. We recommend PSIS-LOO-CV instead of WAIC, \nbecause PSIS provides useful diagnostics and effective sample size and Monte \nCarlo standard error estimates.\n\n\n### Resources\n\n* [mc-stan.org/loo](https://mc-stan.org/loo) (online documentation, vignettes)\n* [Ask a question](https://discourse.mc-stan.org) (Stan Forums on Discourse)\n* [Open an issue](https://github.com/stan-dev/loo/issues) (GitHub issues for bug reports, feature requests)\n\n\n### Installation\n\n* Install the latest release from CRAN:\n\n```r\ninstall.packages(\"loo\")\n```\n\n* Install the latest development version from GitHub:\n\n```r\n# install.packages(\"remotes\")\nremotes::install_github(\"stan-dev/loo\")\n```\n\nWe do _not_ recommend setting `build_vignettes=TRUE` when installing from GitHub\nbecause some of the vignettes take a long time to build and are always available\nonline at [mc-stan.org/loo/articles/](https://mc-stan.org/loo/articles/).\n\n### Python and Matlab/Octave Code\n\nCorresponding Python and Matlab/Octave code can be found at the\n[avehtari/PSIS](https://github.com/avehtari/PSIS) repository.\n\n\n### License\n\nThe code is distributed under the GPL 3 license. The documentation is distributed under the CC BY 4.0 license.\n","funding_links":["https://github.com/sponsors/stan-dev","https://mc-stan.org/support/"],"categories":["R"],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fstan-dev%2Floo","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fstan-dev%2Floo","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fstan-dev%2Floo/lists"}