![[Experimental]](figures/lifecycle-experimental.svg)
Details
formula_status() reports which pieces of the planned hsquared() formula
language are parsed today, reserved as syntax markers, or still roadmap-only.
It is a status table, not a model-fitting helper.
The printed header is derived from the rows being printed, so it cannot
lag the table. Covered-versus-experimental fences live in
$current_behavior and are not dumped into the default print.
Examples
formula_status()
#> <hs_formula_status>
#> default: animal(); cbind()
#> opt-in:
#> permanent(); common_env(); maternal_genetic(); (1 | group);
#> animal(rr()); metafounder(); relmat(); precision(); genomic();
#> single_step()
#> reserved/planned: 14 reserved, 5 planned (error before fitting)
#> fences: $current_behavior
#> term
#> animal(1 | id, pedigree = ped)
#> animal(1 | id) with data = hs_data(..., pedigree = ped)
#> permanent(1 | id)
#> common_env(1 | group)
#> maternal_genetic(1 | dam)
#> (1 | group)
#> animal(rr(covariate, order = 2) | id, pedigree = ped)
#> maternal_env(1 | dam)
#> paternal_genetic(1 | sire, pedigree = ped)
#> paternal_env(1 | sire)
#> group(1 | genetic_group)
#> unknown_parent_group(1 | upg)
#> metafounder(1 | id, pedigree = ped, group = group, Gamma = Gamma)
#> inbreeding(1 | id)
#> cytoplasmic(1 | maternal_line)
#> imprinting(1 | id, pedigree = ped, parent = "maternal")
#> dominance(1 | id, pedigree = ped)
#> epistasis(1 | id, pedigree = ped)
#> relmat(1 | id, K = K)
#> precision(1 | id, Q = Q)
#> genomic(1 | id, Ginv = Ginv)
#> genomic(1 | id, markers = M)
#> single_step(1 | id, Hinv = Hinv)
#> single_step(1 | id, pedigree = ped, markers = M)
#> single_step(1 | id) with data = hs_data(..., pedigree = ped, genotypes = M)
#> single_step(1 | id, pedigree = ped, markers = M, group = group, Gamma = Gamma)
#> markers(M, model = "random")
#> marker_scan(M, map = marker_map)
#> qtl_scan(position, genotype_probs = probs)
#> cbind(trait1, trait2) ~ animal(1 | id, pedigree = ped)
#> animal(trait | id, pedigree = ped, cov = us())
#> animal(trait | id, pedigree = ped, cov = diag())
#> animal(trait | id, pedigree = ped, cov = lowrank(K = 2))
#> animal(trait | id, pedigree = ped, cov = fa(K = 2))
#> missing = miss_control(response = "include")
#> mi(x) with missing = miss_control(predictor = "model")
#> syntax_status fitting_status
#> parsed fitted (v0.1 default)
#> parsed fitted (v0.1 default)
#> parsed fitted (opt-in repeatability)
#> parsed fitted (opt-in common-environment)
#> parsed fitted (opt-in maternal)
#> parsed fitted (opt-in multi-effect)
#> parsed fitted (opt-in random-regression)
#> reserved not available
#> reserved not available
#> reserved not available
#> reserved not available
#> reserved not available
#> parsed fitted (opt-in supplied-Gamma metafounder)
#> reserved not available
#> reserved not available
#> reserved not available
#> reserved not available
#> reserved not available
#> parsed fitted (opt-in supplied relationship, experimental)
#> parsed fitted (opt-in supplied precision, experimental)
#> parsed fitted (opt-in genomic, covered validation-scale)
#> parsed fitted (opt-in genomic / SNP-BLUP)
#> parsed fitted (opt-in single-step)
#> parsed fitted (opt-in single-step construction)
#> parsed fitted (opt-in single-step bundle construction)
#> parsed fitted (opt-in supplied-Gamma H^Gamma)
#> reserved not available
#> reserved not available
#> reserved not available
#> parsed fitted (default route, covered multivariate)
#> planned not available
#> planned not available
#> planned not available
#> reserved not available
#> planned not available
#> planned not available