Sanity check of an sdmTMB model
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.
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