Diagnose a freqTLS fit (frequentist analogue of diagnose_tdt_fit)

The maximum-likelihood analogue of bayesTLS::diagnose_tdt_fit(): where the Bayesian version reports Rhat / ESS / divergences, the freqTLS version reports optimiser convergence, a positive-definite Hessian, and the gradient norm at the optimum, with a single all_pass flag.

Usage

diagnose_tdt_fit(object)

Arguments

object

A freq_tls fit from fit_4pl() (or a profile_tls fit).

Value

A one-row tibble of convergence diagnostics.

See also

fit_4pl(), check_tls()

Examples

raw <- simulate_tls(family = "binomial", CTmax = 36, z = 4, seed = 1)
dat <- standardize_data(
  raw, temp = "temp", duration = "duration",
  n_total = "total", n_surv = "survived"
)
fit <- fit_4pl(dat, family = "binomial", t_ref = 1, quiet = TRUE)
diagnose_tdt_fit(fit)
#> # A tibble: 1 × 9
#>   converged pd_hessian max_abs_gradient gradient_pass optimizer logLik n_params
#>   <lgl>     <lgl>                 <dbl> <lgl>         <chr>      <dbl>    <int>
#> 1 TRUE      TRUE             0.00000617 TRUE          nlminb     -129.        5
#> # ℹ 2 more variables: AIC <dbl>, all_pass <lgl>