posterior_predictive {simmr} | R Documentation |
Plot the posterior predictive distribution for a simmr run
Description
This function takes the output from simmr_mcmc
and plots the
posterior predictive distribution to enable visualisation of model fit.
The simulated posterior predicted values are returned as part of the
object and can be saved for external use
Usage
posterior_predictive(simmr_out, group = 1, prob = 0.5, plot_ppc = TRUE)
Arguments
simmr_out |
A run of the simmr model from |
group |
Which group to run it for (currently only numeric rather than group names) |
prob |
The probability interval for the posterior predictives. The default is 0.5 (i.e. 50pc intervals) |
plot_ppc |
Whether to create a bayesplot of the posterior predictive or not. |
Value
plot of posterior predictives and simulated values
Examples
data(geese_data_day1)
simmr_1 <- with(
geese_data_day1,
simmr_load(
mixtures = mixtures,
source_names = source_names,
source_means = source_means,
source_sds = source_sds,
correction_means = correction_means,
correction_sds = correction_sds,
concentration_means = concentration_means
)
)
# Plot
plot(simmr_1)
# Print
simmr_1
# MCMC run
simmr_1_out <- simmr_mcmc(simmr_1)
# Prior predictive
post_pred <- posterior_predictive(simmr_1_out)
[Package simmr version 0.5.1.216 Index]