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ParetoSmooth

Stable Dev Build Status Coverage Code Style: Blue ColPrac: Contributor's Guide on Collaborative Practices for Community Packages

ParetoSmooth.jl is a Julia package for efficient approximate leave-one-out cross-validation for fitted Bayesian models. We compute LOO-CV using Pareto smoothed importance sampling (PSIS), a modification of importance sampling. More details can be found in Vehtari, Gelman, and Gabry (2017).

If you use this library, please remember to cite both:

@misc{ParetoSmooth.jl,
	author  = {Carlos Parada <cdp49@cam.ac.uk>},
	title   = {ParetoSmooth.jl},
	url     = {https://github.com/TuringLang/ParetoSmooth.jl},
	version = {v0.7.1},
	year    = {2021},
	month   = {6}
}

and:

@Article{Vehtari2017,
  author={Vehtari, Aki
  and Gelman, Andrew
  and Gabry, Jonah},
  title={Practical Bayesian model evaluation using leave-one-out cross-validation and WAIC},
  journal={Statistics and Computing},
  year={2017},
  month={Sep},
  day={01},
  volume={27},
  number={5},
  pages={1413-1432},
  issn={1573-1375},
  doi={10.1007/s11222-016-9696-4},
  url={https://doi.org/10.1007/s11222-016-9696-4}
}