Comprehensive model checking

The tulpa::check_model() method for tobs_fit: the criteria, the posterior-predictive check and the goodness-of-fit tests in one call, printed as a report and drawn as the diagnostic panel.

Usage

# S3 method for class 'tobs_fit'
check_model(
  object,
  coords = NULL,
  n.samples = 250,
  nsim = NULL,
  seed = NULL,
  plot = TRUE,
  ...
)

Arguments

object

A tobs_fit object.

coords

Optional n_sites x 2 coordinate matrix. Adds Moran's I on the occupancy residuals and the correlogram panel.

n.samples

Posterior samples for simulation tests.

nsim

The same budget under the name tulpa::check_model()'s default uses; overrides n.samples when given.

seed

Optional random seed for the simulation tests; the caller's RNG stream is restored afterwards.

plot

Draw the panel. FALSE prints the report alone, for a log or a headless run.

...

Must be empty; an unrecognised argument is an error.

Value

Invisibly, the diagnostic results: waic, dic, cpo, ppc, zero_inflation, dispersion, pit, uniformity, and moran when coords is supplied.

Details

The engine's default method builds its panel from fitted() and residuals() as numeric vectors, which a latent-state fit does not have – fitted() returns list(psi, p, z) and residuals() one series per process, so the response cannot be resolved. This method reads the same quantities through the family's own doors instead: pit_residuals(), ppc(), test_dispersion() and tulpa::moran_i().