tisis.md
In loo: Efficient Leave-One-Out Cross-Validation and WAIC for Bayesian Models

tis throws correct errors and warnings

Code
  psis(-LLarr, r_eff = r_eff_arr)
Message
  Replacing NAs in `r_eff` with 1s
Output
  Computed from 1000 by 32 log-weights matrix.
  MCSE and ESS estimates assume MCMC draws (r_eff in [0.6, 1.0]).

  All Pareto k estimates are good (k < 0.67).
  See help('pareto-k-diagnostic') for details.

tis_loo and sis_loo are returned

Code
  print(loo_tis)
Output

  Computed from 1000 by 32 log-likelihood matrix using tis_loo .

           Estimate  SE
  elpd_loo    -83.6 4.3
  p_loo         3.3 1.2
  looic       167.2 8.6
  ------

Code
  print(loo_sis)
Output

  Computed from 1000 by 32 log-likelihood matrix using sis_loo .

           Estimate  SE
  elpd_loo    -83.6 4.3
  p_loo         3.3 1.2
  looic       167.2 8.6
  ------