simmr: posterior_predictive – R documentation

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posterior_predictive

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 `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.

Examples

## Not run: 
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)

## End(Not run)

simmr

A Stable Isotope Mixing Model

v0.4.5

GPL (>= 2)

Authors

Andrew Parnell

Initial release

2021-02-28