Sanity check of an sdmTMB model

Usage

sanity(object, big_sd_log10 = 2, gradient_thresh = 0.001, silent = FALSE)

Arguments

object: Fitted model from sdmTMB().
big_sd_log10: Value to check size of standard errors against. A value of 2 would indicate that standard errors greater than 10^2 (i.e., 100) should be flagged.
gradient_thresh: Gradient threshold to issue warning.
silent: Logical: suppress messages? Useful to set to TRUE if running large numbers of models and just interested in returning sanity list objects.

Value

An invisible named list of checks.

Details

If object is NA, NULL, or of class "try-error", sanity() will return FALSE. This is to facilitate using sanity() on models with try() or tryCatch(). See the examples section.

Examples

fit <- sdmTMB(
  present ~ s(depth),
  data = pcod_2011, mesh = pcod_mesh_2011,
  family = binomial()
)
sanity(fit)
#> ✔ Non-linear minimizer suggests successful convergence
#> ✔ Hessian matrix is positive definite
#> ✔ No extreme or very small eigenvalues detected
#> ✔ No gradients with respect to fixed effects are >= 0.001
#> ✔ No fixed-effect standard errors are NA
#> ✔ No standard errors look unreasonably large
#> ✔ No sigma parameters are < 0.01
#> ✔ No sigma parameters are > 100
#> ✔ Range parameter doesn't look unreasonably large

s <- sanity(fit)
#> ✔ Non-linear minimizer suggests successful convergence
#> ✔ Hessian matrix is positive definite
#> ✔ No extreme or very small eigenvalues detected
#> ✔ No gradients with respect to fixed effects are >= 0.001
#> ✔ No fixed-effect standard errors are NA
#> ✔ No standard errors look unreasonably large
#> ✔ No sigma parameters are < 0.01
#> ✔ No sigma parameters are > 100
#> ✔ Range parameter doesn't look unreasonably large
s
#> $hessian_ok
#> [1] TRUE
#> 
#> $eigen_values_ok
#> [1] TRUE
#> 
#> $nlminb_ok
#> [1] TRUE
#> 
#> $range_ok
#> [1] TRUE
#> 
#> $gradients_ok
#> [1] TRUE
#> 
#> $se_magnitude_ok
#> [1] TRUE
#> 
#> $se_na_ok
#> [1] TRUE
#> 
#> $sigmas_ok
#> [1] TRUE
#> 
#> $all_ok
#> [1] TRUE
#> 

# If fitting many models in a loop, you may want to wrap
# sdmTMB() in try() to handle errors. sanity() will take an object
# of class "try-error" and return FALSE.
# Here, we will use stop() to simulate a failed sdmTMB() fit:
failed_fit <- try(stop())
#> Error in try(stop()) : 
s2 <- sanity(failed_fit)
all(unlist(s))
#> [1] TRUE
all(unlist(s2))
#> [1] FALSE