About Anaconda Help Download Anaconda

Efficient approximate leave-one-out cross-validation (LOO) for Bayesian models fit using Markov chain Monte Carlo. The approximation uses Pareto smoothed importance sampling (PSIS), a new procedure for regularizing importance weights. As a byproduct of the calculations, we also obtain approximate standard errors for estimated predictive errors and for the comparison of predictive errors between models. The package also provides methods for using stacking and other model weighting techniques to average Bayesian predictive distributions.

copied from cf-post-staging / r-loo
Type Size Name Uploaded Downloads Labels
conda 1.8 MB | noarch/r-loo-2.6.0-r43hc72bb7e_2.conda  1 year and 3 months ago 1342 main
conda 1.8 MB | noarch/r-loo-2.6.0-r44hc72bb7e_2.conda  1 year and 3 months ago 1102 main
conda 1.8 MB | noarch/r-loo-2.6.0-r43hc72bb7e_1.conda  2 years and 3 months ago 4050 main
conda 1.8 MB | noarch/r-loo-2.6.0-r42hc72bb7e_1.conda  2 years and 3 months ago 5066 main
conda 1.8 MB | noarch/r-loo-2.6.0-r42hc72bb7e_0.conda  2 years and 6 months ago 2376 main
conda 1.8 MB | noarch/r-loo-2.6.0-r41hc72bb7e_0.conda  2 years and 6 months ago 3264 main

© 2025 Anaconda, Inc. All Rights Reserved. (v4.2.2) Legal | Privacy Policy