posterior_predictive: Plot the posterior predictive distribution for a simmr run

In simmr: A Stable Isotope Mixing Model

Plot the posterior predictive distribution for a simmr run

Description

This function takes the output from simmr_mcmcand 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 simmr_mcmc
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)

simmr documentation built on Nov. 2, 2023, 6:08 p.m.