predict.emc.prior {EMC2} | R Documentation |
Generate Posterior/Prior Predictives
Description
Simulate n_post
data sets using the posterior/prior parameter estimates
Usage
## S3 method for class 'emc.prior'
predict(object, data = NULL, n_post = 50, n_cores = 1, n_trials = NULL, ...)
## S3 method for class 'emc'
predict(
object,
hyper = FALSE,
n_post = 50,
n_cores = 1,
stat = c("random", "mean", "median")[1],
...
)
Arguments
object |
An emc or emc.prior object from which to generate predictives |
data |
A data frame needed to exactly match the original design |
n_post |
Integer. Number of generated datasets |
n_cores |
Integer. Number of cores across which there should be parallellized |
n_trials |
An integer. If |
... |
Optional additional arguments passed to |
hyper |
Boolean. Defaults to |
stat |
Character. Can be |
Value
A list of simulated data sets of length n_post
Examples
# based on an emc object ran by fit() we can generate posterior predictives
predict(samples_LNR, n_cores = 1, n_post = 10)