idealstan
objectsThis function will draw from the posterior distribution, whether in terms of the outcome (prediction) or to produce the log-likelihood values.
This function can also produce either distribution of the
outcomes (i.e., predictions) or the log-likelihood values of the posterior (set option
type
to 'log_lik'
.
For more information, see the package vignette How to Evaluate Models.
You can then use functions such as
id_plot_ppc
to see how well the model does returning the correct number of categories
in the score/vote matrix.
Also see help("posterior_predict", package = "rstanarm")
# S4 method for idealstan
id_post_pred(object, draws = 100,
output = "observed", type = "predict", sample_scores = NULL, ...)
A fitted idealstan
object
The number of draws to use from the total number of posterior draws (default is 100).
If the model has an unbounded outcome (Poisson, continuous, etc.), then
specify whether to show the 'observed'
data (the default) or the binary
output 'missing'
showing whether an observation was predicted as missing or not
Whether to produce posterior predictive values ('predict'
, the default),
or log-likelihood values ('log_lik'
). See the How to Evaluate Models vignette for more info.
In addition to reducing the number of posterior draws used to calculate the posterior predictive distribution, which will reduce computational overhead. Only available for calculating predictive distributions, not log-likelihood values.
Any other arguments passed on to posterior_predict (currently none available)