Posterior Predictive Check

Generate posterior predictive checks for a fitted ratio model. Compares observed data to replicated data from the posterior predictive distribution.

Usage

# S3 method for class 'ratiod_fit'
pp_check(
  object,
  type = c("dens_overlay", "scatter", "intervals", "stat"),
  component = c("numerator", "denominator", "both"),
  stat = mean,
  ndraws = 50,
  ...
)

Arguments

object

A ratiod_fit object

type

Type of check: "dens_overlay", "scatter", "intervals", "stat"

component

Which component: "numerator", "denominator", or "both"

stat

Function for "stat" type (default: mean)

ndraws

Number of posterior draws to replicate (default: 50)

...

Additional arguments passed to bayesplot functions

Value

A ggplot object

Examples

# \donttest{
# Simulate data and fit model
set.seed(123)
n <- 50
df <- data.frame(
  count = rnbinom(n, size = 5, mu = 15),
  total = rnbinom(n, size = 8, mu = 100),
  x = rnorm(n),
  site = factor(rep(1:10, each = 5))
)
fit <- tratio(
  count | total ~ x + (1 | site),
  data = df,
  family = ratiod_negbin_negbin(),
  control = list(iter = 400, chains = 1, seed = 1)
)
# Density overlay of replicated against observed numerators
pp_check(fit, type = "dens_overlay")

# }