Summarise a mcmc_fit object
# S3 method for mcmc_fit
summary(object, n_pars = 8, ...)An object of class mcmc_fit.
The number of pi/theta parameters and z 'items' to display.
Other arguments passed to function.
For the class conditional model the 'full' theta parameterisation (i.e. appearing to have the same number of parameters as the standard Dawid-Skene model) is calculated and returned. This is designed to allow easier comparison with the full Dawid-Skene model.
# \donttest{
fit <- rater(anesthesia, "dawid_skene", verbose = FALSE)
summary(fit)
#> Model:
#> Bayesian Dawid and Skene Model
#>
#> Prior parameters:
#>
#> alpha: default
#> beta: default
#>
#> Fitting method: MCMC
#>
#> pi/theta samples:
#> mean 5% 95% Rhat ess_bulk
#> pi[1] 0.37 0.27 0.49 1 8622.57
#> pi[2] 0.41 0.30 0.52 1 8507.02
#> pi[3] 0.14 0.07 0.23 1 6267.10
#> pi[4] 0.07 0.03 0.14 1 7660.54
#> theta[1, 1, 1] 0.86 0.79 0.93 1 9185.09
#> theta[1, 1, 2] 0.10 0.05 0.17 1 8784.51
#> theta[1, 1, 3] 0.02 0.00 0.05 1 5834.04
#> theta[1, 1, 4] 0.02 0.00 0.05 1 6508.08
#> # ... with 76 more rows
#>
#> z:
#> MAP Pr(z = 1) Pr(z = 2) Pr(z = 3) Pr(z = 4)
#> z[1] 1 1.00 0.00 0.00 0.00
#> z[2] 3 0.00 0.00 0.98 0.02
#> z[3] 2 0.40 0.60 0.00 0.00
#> z[4] 2 0.01 0.99 0.00 0.00
#> z[5] 2 0.00 1.00 0.00 0.00
#> z[6] 2 0.00 1.00 0.00 0.00
#> z[7] 1 1.00 0.00 0.00 0.00
#> z[8] 3 0.00 0.00 1.00 0.00
#> # ... with 37 more items
# }