Summarise an optim_fit object
# S3 method for optim_fit
summary(object, n_pars = 8, ...)An object of class optim_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", method = "optim")
summary(fit)
#> Model:
#> Bayesian Dawid and Skene Model
#>
#> Prior parameters:
#>
#> alpha: default
#> beta: default
#>
#> Fitting method: Optimisation
#>
#> pi/theta estimates:
#> mean
#> pi[1] 0.38
#> pi[2] 0.43
#> pi[3] 0.13
#> pi[4] 0.06
#> theta[1, 1, 1] 0.91
#> theta[1, 1, 2] 0.09
#> theta[1, 1, 3] 0.00
#> theta[1, 1, 4] 0.00
#> # ... 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 0
#> z[2] 3 0.00 0.00 1 0
#> z[3] 2 0.02 0.98 0 0
#> z[4] 2 0.00 1.00 0 0
#> z[5] 2 0.00 1.00 0 0
#> z[6] 2 0.00 1.00 0 0
#> z[7] 1 1.00 0.00 0 0
#> z[8] 3 0.00 0.00 1 0
#> # ... with 37 more items
#>
#> Log probability: -238.0047
#> Fit converged: TRUE
# }