How to compute SE as in loo package

[avehtari]

See Vehtari, Gelman and Gabry (2017). Practical Bayesian model evaluation using leave-one-out cross-validation and WAIC. In Statistics and Computing, 27(5):1413–1432. doi:10.1007/s11222-016-9696-4. Preprint

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SE of elpd_loo - loo package

It seems there is some confusion with the terms. Likelihood is a function of parameters. \widehat{\mathrm{elpd}}_{\mathrm{loo},i} are log predictive densities (or log predictive probabilities). Eqs 22 and 23 do not include estimation errors for individual \widehat{\mathrm{elpd}}_{\mathrm{loo},i}. We do mention in the paragraph starting at the bottom of page 19 and continuing at the top of page 20, that we could compute the Monte Carlo estimation errors for individual terms, too, and loo >2.0.…