Sanity check of sdmTMB model

## Arguments

- fit
Fitted model from

`sdmTMB()`

- big_sd_log10
Value to check size of standard errors against. A value of 3 would indicate that standard errors greater than

`10^3`

should be flagged.- gradient_thresh
Gradient threshold to issue warning

## 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
#>
```