Skip to contents

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. Full q4 unstructured and phylogenetic correlation summaries are derived targets; direct SD and scale targets can still fail on a weak, boundary-limited, or one-sided profile.

Usage

profile_targets(object, ready_only = FALSE)

Arguments

object

A drmTMB fit.

ready_only

Logical; if TRUE, return only targets whose profile_ready column is TRUE.

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 "direct" for a target that maps to a single fitted TMB parameter, "derived" for a transformed or multi-parameter quantity, or "constrained" for a target that needs a model-specific constrained profile. profile_ready = TRUE means the target is direct or constrained 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", "point_fit_only_zi_nbinom2_sigma_q1", "point_fit_only_zero_one_beta_phylo_q1", "point_fit_only_zero_one_beta_phylo_zoi_q1", "point_fit_only_zero_one_beta_phylo_coi_q1", "point_fit_only_zero_one_beta_animal_q1", "point_fit_only_zero_one_beta_animal_zoi_q1", "point_fit_only_zero_one_beta_animal_coi_q1", "point_fit_only_zero_one_beta_relmat_q1", "point_fit_only_zero_one_beta_relmat_zoi_q1", "point_fit_only_zero_one_beta_relmat_coi_q1", "point_fit_only_zero_one_beta_spatial_q1", "point_fit_only_zero_one_beta_phylo_interaction_q1", "point_fit_only_zero_one_beta_phylo_interaction_zoi_q1", "point_fit_only_zero_one_beta_phylo_interaction_coi_q1", "point_fit_only_zero_one_beta_zoi_q1", "point_fit_only_zero_one_beta_coi_q1", "derived_target", and "derived_unstructured_correlation". A point_fit_only_* note records a direct point-estimate target that is deliberately unavailable to profiling: the zi-nbinom2 note covers the ordinary q1 scale route, and the zero-one-beta notes cover that bounded family's structured q1 mean route and its zero- and one-inflation routes. Derived variance-ratio summaries such as total_variance_share and phylo_total_variance_share are listed as point-estimate targets with profile_ready = FALSE.

Details

Use ready_only = TRUE for the fastest inspection path before calling confint(..., method = "profile"). Use the target_class column to filter fixed effects, random-effect SDs, residual correlations, and other variance-component rows before a long profile run.

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  0.59000000      0.590000     link linear_predictor      direct
#> 2     2  0.42000000      0.420000     link linear_predictor      direct
#> 3     1 -2.70183894     -2.701839     link linear_predictor      direct
#> 4     1  0.06708204     -2.701839 response              exp      direct
#>   profile_ready profile_note
#> 1          TRUE        ready
#> 2          TRUE        ready
#> 3          TRUE        ready
#> 4          TRUE        ready
profile_targets(fit, ready_only = TRUE)
#>                      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  0.59000000      0.590000     link linear_predictor      direct
#> 2     2  0.42000000      0.420000     link linear_predictor      direct
#> 3     1 -2.70183894     -2.701839     link linear_predictor      direct
#> 4     1  0.06708204     -2.701839 response              exp      direct
#>   profile_ready profile_note
#> 1          TRUE        ready
#> 2          TRUE        ready
#> 3          TRUE        ready
#> 4          TRUE        ready