View source: R/prior_viz.simmr_output.R
| prior_viz | R Documentation | 
This function takes the output from simmr_mcmc or
simmr_ffvb and plots the prior distribution to enable visual
inspection. This can be used by itself or together with
posterior_predictive to visually evaluate the influence of
the prior on the posterior distribution.
prior_viz(
  simmr_out,
  group = 1,
  plot = TRUE,
  include_posterior = TRUE,
  n_sims = 10000,
  scales = "free"
)
| simmr_out | A run of the simmr model from  | 
| group | Which group to run it for (currently only numeric rather than group names) | 
| plot | Whether to create a density plot of the prior or not. The simulated prior values are returned as part of the object | 
| include_posterior | Whether to include the posterior distribution on top of the priors. Defaults to TRUE | 
| n_sims | The number of simulations from the prior distribution | 
| scales | The type of scale from  | 
A list containing plot: the ggplot object (useful if requires customisation), and sim: the simulated prior values which can be compared with the posterior densities
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
prior <- prior_viz(simmr_1_out)
head(prior$p_prior_sim)
summary(prior$p_prior_sim)
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