profile_targets() shows the names that can be supplied to
confint.drmTMB(). The table also records whether each row is currently
ready for direct profile-likelihood intervals. This helps users inspect the
fitted object before starting an expensive profile.
Value
A data frame with columns parm, target_class, dpar, term,
tmb_parameter, index, estimate, link_estimate, scale,
transformation, target_type, profile_ready, and profile_note.
target_type is either "direct" for a target that maps to a single
fitted TMB parameter or "derived" for a target that is reported from a
transformed or multi-parameter quantity. profile_ready = TRUE means the
target is direct and the fitted object retained the TMB object needed for
confint.drmTMB() with method = "profile". Common profile_note
values are "ready", "tmb_object_required", "missing_tmb_parameter",
"derived_target", and "derived_unstructured_correlation".
Derived variance-ratio summaries such as repeatability and phylogenetic
signal are listed as point-estimate targets with
profile_ready = FALSE.
Examples
dat <- data.frame(y = c(0.2, 0.5, 1.1, 1.4), x = c(-1, 0, 1, 2))
fit <- drmTMB(bf(y ~ x, sigma ~ 1), data = dat)
profile_targets(fit)
#> parm target_class dpar term tmb_parameter
#> 1 fixef:mu:(Intercept) fixed-effect mu (Intercept) beta_mu
#> 2 fixef:mu:x fixed-effect mu x beta_mu
#> 3 fixef:sigma:(Intercept) fixed-effect sigma (Intercept) beta_sigma
#> 4 sigma distributional-scale sigma (constant) beta_sigma
#> index estimate link_estimate scale transformation target_type
#> 1 1 0.59000002 0.590000 link linear_predictor direct
#> 2 2 0.42000003 0.420000 link linear_predictor direct
#> 3 1 -2.70183847 -2.701838 link linear_predictor direct
#> 4 1 0.06708207 -2.701838 response exp direct
#> profile_ready profile_note
#> 1 TRUE ready
#> 2 TRUE ready
#> 3 TRUE ready
#> 4 TRUE ready