Implementation map

How to read the project maps

The public site has three maps with different jobs. Use model-map when the question is “what should I fit?”. Use this implementation map when the question is “is this surface fitted or planned?”. Use the source map when the question is “where are the code, tests, and docs?”. The validation-debt register is the evidence ledger behind these pages. Contributor design ledgers record sequence and future work; they are not the current-status authority.

When you are closing out a slice from this ledger and need to plot its recovery evidence, see Simulation plot grammar for the shared bias/RMSE/coverage display contract.

Every status row should be read across the same dimensions:

Dimension	What it records
Family or component	Gaussian, Poisson, NB2, ordinal, zi, hu, shape, known V, or another fitted component.
Dependence layer	ordinary group, phylogenetic, coordinate spatial, animal, relmat(), known sampling covariance, or residual rho12.
Formula route	The public syntax that fits the row, such as (1 + x | id), spatial(1 | p | site, coords = coords), or rho12 ~ x.
q or endpoint class	q=1 intercept, independent slope, q=2, q>2, q=4, or future p8/q8 endpoint work.
Random-effect scope	Whether random intercepts, random slopes, and cross-parameter or bivariate combinations are fitted, first-slice, planned, or blocked.
Extractor route	Which of summary()$parameters, summary()$covariance, ranef()$terms, corpairs(), profile_targets(), and check_drm() exposes the result.
Evidence tier	Whether the surface has smoke evidence, artifact writers, small-grid admission, formal operating-characteristic evidence, or only diagnostic/failure-ledger evidence.
Interval tier	Whether intervals are fast Wald, direct profile-ready, profile-proven, direct bootstrap, derived-unavailable, private bootstrap smoke, not requested, or unavailable.
User route	What to fit now, and what smaller fitted route to use when the requested model is planned.

Simulation and interval evidence are deliberately separate from fitted support. A model can be fitted and still have only smoke or diagnostic evidence.

Evidence tier	Meaning
Formal small grid	Likelihood, parser, extractors, diagnostics, interval status, focused recovery tests, and an ADEMP sheet exist.
Smoke/artifact only	The route is fitted and inspectable, but it does not yet have enough recovery or coverage evidence for broad claims.
Interval-heavy opt-in	Profiles or bootstrap checks are expensive or partial; status tables must show success, failure, or not-requested rows.
Diagnostic/failure ledger	The fit teaches us about boundaries or hard cases, but it is not a user-facing operating-characteristic claim.
Planned/blocked	Syntax or design may exist, but the fitter should reject the route or route users to a supported alternative.

Use fast Wald intervals for routine fixed-effect coefficients and selected direct fitted targets when TMB::sdreport() supplies the optimized-parameter covariance. Direct SD intervals use the fitted log-SD scale before exponentiating, and direct correlation intervals use the guarded atanh correlation-link scale before returning to the correlation scale. Do not use Wald intervals as a shortcut for derived q=4 correlations, repeatability, phylogenetic signal, unavailable rows, or weak-Hessian fits that need fit-specific diagnostics. Direct profile targets can be mechanically available but still fail in a given fit. confint(method = "bootstrap") now provides a narrow public simulate/refit route for selected direct targets, while Phase 18 bootstrap artifacts remain private simulation infrastructure and do not imply bootstrap support in summary(), corpairs(), prediction tables, or derived summaries.

Family and component map

Use this table before combining a family with a random-effect or dependence surface.

Model family or component	Fitted formulas today	Random effects today	Dependence or correlation today	Main planned boundary
Gaussian, one response	mu and sigma	ordinary mu intercepts, independent slopes, one-slope correlated blocks, q > 2 numeric mu blocks, sigma intercepts, independent sigma slopes, unlabelled correlated sigma intercept-slope and multi-slope blocks, and sd(group) ~ x for unlabelled mu intercept SDs	ordinary group-level corpairs() rows for fitted covariance blocks	labelled or cross-formula sigma slope covariance, coefficient-specific sd(group, coef = "x"), and broad p8 location-scale slope endpoints
Student-t	fixed-effect mu, sigma, and nu	ordinary unlabelled mu random intercepts and independent numeric slopes	the spatial() q1 mu intercept and phylo() nu intercept are diagnostic-only; the spatial intercept-plus-one-slope route is recovery-grade; no labelled covariance	sigma or other nu random effects, correlated slopes, skewness, and structured Student-t effects beyond those exact gates
Lognormal and Gamma	fixed-effect mu and family-specific sigma scale	separate gates for ordinary unlabelled mu random intercepts/independent numeric slopes or one ordinary sigma random intercept; the two sides cannot be combined	lognormal sigma intercept is inference-ready with caveats only in its exact ledger domain; Gamma sigma intercept is inference-ready with caveats only at true SD 0.40, n_each=12, and M >= 32 (M=16 borderline); Gamma also has a recovery-grade relmat() q=1 mu intercept/one-slope	sigma slopes, combined mu+sigma random effects, correlated or labelled slopes, known covariance, and further structured dependence
Beta	fixed-effect mu and sigma	ordinary unlabelled mu random intercepts and independent numeric slopes	recovery grade: animal() q=1 mu intercept/one-slope and sigma intercept	ordinary sigma random effects, correlated slopes, bounded-response known covariance, and further structured dependence
Tweedie	fixed-effect mu, sigma, and intercept-only nu ~ 1	ordinary unlabelled mu random intercepts and independent numeric slopes; exact mc-0539 is inference-ready with caveats for true SD 0.50 and M>=16	none	predictor-dependent power, sigma random effects, correlated/labelled mu slopes, structured dependence, and bivariate or mixed-response Tweedie
Zero-one beta	fixed-effect mu, sigma, zoi, and coi	ordinary unlabelled mu random intercepts and independent numeric slopes; exact mc-0575 is inference-ready with caveats for true SD 0.50 and M>=16, under its generator-qualified evidence; exact ordinary zoi ~ 1 + (1 | id), same-raw-symbol zoi ~ x + (0 + x | id), coi ~ 1 + (1 | id), and same-raw-symbol coi ~ x + (0 + x | id) are point-fit-only	no direct profile, interval, or coverage claim for the atom-side q1 gates; the coi routes have population-level recovery at M = 64, 50 observations/group, with sparse-atom and boundary-predictor-spread conditional-mode warnings	transformed or mismatched atom slopes, other zoi random effects, covariance blocks, known covariance, denominator syntax, bivariate bounded responses, and structured dependence
Beta-binomial	fixed-effect mu and sigma with row trials	ordinary unlabelled mu random intercepts and independent numeric slopes	none	correlated slopes, sigma random effects, zero-one inflation, and structured dependence
Binomial	fixed-effect mu for 0/1 or cbind(successes, failures) responses	ordinary unlabelled mu random intercepts and independent numeric slopes	the exact independent-slope ledger domain is inference-ready with caveats	correlated or labelled slopes, structured effects, non-logit links, and bivariate or mixed responses
Poisson and NB2	fixed-effect mu; NB2 also has fixed-effect sigma and the first ordinary log-sigma random-intercept gate	ordinary non-zero-inflated mu random intercepts/slopes; Poisson/NB2 single-provider q1 structured mu; NB2 q1 structured sigma; one exact crossed NB2 spatial-plus-relatedness mu route	single-provider routes have row-specific source/smoke/recovery evidence; the exact crossed NB2 route is recovery-only with no intervals or coverage	correlated ordinary count slopes, unsupported inflation/hurdle count-mu effects, plain NB2 sigma slopes, richer/labelled structured routes, simultaneous structured types beyond the exact crossed NB2 gate, and broader count covariance
Zero-inflated Poisson and zero-inflated NB2	fixed-effect mu; zi ~ ...; NB2 also has fixed-effect sigma	exact diagnostic-only q=1 Poisson zi ~ spatial(1 | id, coords = coords) intercept only	same exact structured intercept only (no NB2 zi structure)	random effects in zi beyond the exact Poisson spatial intercept, structured zero inflation beyond the Poisson zi ~ spatial() intercept, NB2 zi structure, and corpairs() for count latent effects
Truncated NB2 and hurdle NB2	fixed-effect mu; fixed-effect sigma; hurdle NB2 also has hu ~ ...	ordinary unlabelled zero-truncated NB2 mu random intercepts and independent numeric slopes for non-hurdle models	diagnostic-only: one relmat() q=1 hu intercept with K or Q (hurdle NB2, inherited by the alias)	random effects in hu beyond the exact relmat() q=1 intercept, random effects in hurdle count mu, correlated zero-truncated slopes, and other structured hurdle effects
Cumulative-logit ordinal	fixed-effect ordinal location with estimated cutpoints	ordinary unlabelled mu random intercepts and independent numeric slopes, plus one exact q1 mu ~ phylo(1 | id, tree = tree) intercept	exact phylogenetic intercept is diagnostic-only	other structured ordinal effects, scale or discrimination formulas, intervals/coverage for the phylogenetic gate, and bivariate ordinal models
Gaussian meta-analysis	meta_V(V = V) or deprecated compatibility alias meta_known_V(V = V)	ordinary Gaussian random effects may be combined with estimated residual terms where supported	known sampling covariance is observation-level input, not a weight or latent relatedness effect; vector and dense V routes are implemented and tested, but their capability tier is unregistered	non-Gaussian known covariance, proportional-variance meta_V(w = w), sparse/block-sparse known covariance, and dense known V with non-unit weights
Bivariate Gaussian	mu1, mu2, sigma1, sigma2, and fixed-effect rho12	ordinary bivariate random-intercept slices, same-response mu/sigma intercept and slope-only covariance, all-four q=4 intercept blocks, matching slope-only mu1/mu2 and sigma1/sigma2 blocks, matching q4/q6 mu1/mu2 location blocks with smoke artifact routing, and the first ordinary q8 all-endpoint block with smoke/recovery artifact routing	residual rho12() and group-level corpairs() stay separate	random effects in rho12, mixed-response bivariate families, broader p8/q8 endpoint variants, and broad q > 2 recovery

zi is currently a fixed-effect probability component except for the exact diagnostic-only Poisson spatial q=1 intercept. hu is fixed-effect by default, with one diagnostic-only truncated-NB2 q=1 hu ~ relmat(1 | id, K/Q = ...) intercept route. Do not infer other random-effect or structured-dependence support from either narrow gate.

Current capability and evidence map

This table connects fitted status to inference status. A first-slice fitted row is useful, but it is not the same as a formal coverage claim.

Surface	Intercepts	Slopes	Combinations	Simulation or evidence tier	Interval tier
Ordinary Gaussian mu	fitted	independent, one correlated slope, q>2 advanced	ordinary group covariance	formal small grids for named subsets; q>2 remains advanced	direct SD/profile targets; q>2 correlations derived-unavailable
Ordinary Gaussian sigma	fitted	independent plus unlabelled correlated log(sigma) intercept-slope and multi-slope blocks	labelled blocks and cross-formula mu-sigma slope covariance remain planned	smoke and small-grid evidence for named independent routes; correlated blocks have fit/extractor contracts but no blanket interval claim	direct SD targets and Wald fixed effects where row-specific evidence allows
sd(group)	fitted for unlabelled Gaussian mu intercept SD	no coefficient-specific slope SD yet	direct SD surface	focused recovery	coefficient intervals only where direct; row-specific SDs are derived
Bivariate ordinary Gaussian	q=2 intercepts fitted	matching slope-only mu1/mu2, same-response q2 mu/sigma, q2 sigma1/sigma2, q4/q6 location mu1/mu2, and the first ordinary q8 all-endpoint block fitted	selected q=2, same-response mu/sigma, all-four q=4 intercept blocks, q > 2 location blocks, and the first q8 endpoint block	q=2 admitted; same-response q2 and q2 scale-slope artifact-backed; q4/q6 location smoke only; q8 diagnostic artifacts only, with no coverage or power claim	q=2 direct profile; q > 2 location SDs and q8 endpoint SDs direct; q > 2 and q8 correlations derived-unavailable
Residual rho12	not a random effect	predictor-dependent fixed effects	residual coscale only	admitted and interval-heavy	default direct Wald for constant rows; direct profile for constant or supplied newdata rows; direct bootstrap only through selected confint() targets
Phylogenetic Gaussian	mu intercept fitted	one mu slope fitted	q=2 mu1/mu2 and q=4 location-scale fitted, with Ayumi hard cases diagnostic	small controlled grids; full-species hard cases stay diagnostic	direct targets for q=2; q=4 derived-unavailable
Coordinate spatial Gaussian	mu intercept fitted	one mu slope fitted	q=2 mu1/mu2 fitted; constant all-four q=4 fitted	q=2 admitted; q=4 extractor/diagnostic smoke only	fixed-effect Wald and opt-in profiles for q=2 artifacts; q=4 derived-unavailable
Animal Gaussian	mu intercept fitted	one mu slope fitted	q=2 and q=4 fitted for small dense or known-matrix routes	q=2/q=4 smoke artifacts, not broad coverage	q=2 fixed-effect Wald plus opt-in profile status; q=4 derived-unavailable
relmat() Gaussian	mu intercept fitted	one mu slope fitted	q=2 and q=4 fitted for known matrices	q=2/q=4 smoke artifacts, not broad coverage	same as animal
Poisson/NB2 ordinary mu	fitted	independent numeric slopes fitted	no labelled or correlated count blocks	first small count grids	Wald fixed effects; direct SD profile artifacts
NB2 ordinary sigma	fitted for independent log-sigma random intercepts	no plain sigma slopes yet	recovery-grade q=1 structured sigma one-slope slices (phylo()/spatial()/animal()/relmat()); no labelled, joint mu/sigma, zero-inflated, truncated, or hurdle scale blocks	separate overdispersion-random-intercept smoke lane	Direct log_sd_sigma profile target
Non-Gaussian structured dependence	Poisson/NB2 q1 single-provider mu routes, NB2 q1 structured sigma, and one exact crossed NB2 spatial-plus-relatedness mu route	unlabelled single-provider intercept-plus-one-slope blocks are fitted; the crossed two-provider route is intercept-only on each field	pure, labelled, or multiple slopes, richer covariance, and simultaneous providers beyond the exact crossed gate remain planned	focused tests cover extraction/diagnostics; the crossed design has recovery-only evidence	Direct log_sd_phylo targets where exposed; no crossed-route interval/coverage promotion
zi, hu, zoi, and coi	fixed effects where supported	diagnostic-only q=1 intercept gates for Poisson zi ~ spatial() and truncated-NB2 hu ~ relmat(K/Q); point-fit-recovery zero-one-beta zoi and coi q1 intercept/same-raw-symbol slope gates	no labelled or correlated covariance layer	fixed-effect tests plus focused route tests; the exact zero-one-beta atom gates have independent likelihood and retained recovery evidence	Wald fixed effects where implemented; zero-one-beta atom q1 remains point-fit-only, with profiles, intervals, and coverage unavailable
Ordinal, shape, bounded scale	fixed effects where supported; eligible cumulative-logit, Student-t, beta, Tweedie, skew-normal, and zero-one-beta routes also fit ordinary mu intercepts/slopes	diagnostic-only cumulative-logit q1 mu ~ phylo(); recovery-grade Student-t mu ~ spatial(1 + x | ...) and beta mu/sigma ~ animal() gates; Student-t intercept-only mu ~ spatial(1 | ...) and nu ~ phylo() are diagnostic-only	other distributional-parameter random effects, correlated/labelled slopes, and structured neighbours beyond the exact gates remain planned	family recovery tests plus route-specific source/local-fit tests	retain each live-ledger tier; no blanket recovery, interval, or coverage promotion
meta_V(V = V)	estimated effects plus known sampling covariance	ordinary Gaussian random effects only where otherwise supported	V is input data, not a weight or latent dependence; vector and dense forms are implemented and tested, but their capability tier is unregistered	no interval or coverage claim for this route; predictor-dependent sigma needs fit-specific Hessian checks	never interval-target V; Wald SEs and intervals for sigma ~ moderator are unreliable when pdHess = FALSE

Random-effect and dependence map

Here q is the number of latent endpoints in one covariance block. A q=2 block has two endpoints, such as mu1 and mu2 random intercepts. A q=4 block has four endpoints, such as mu1, mu2, sigma1, and sigma2 random intercepts. The q8 language now includes one fitted ordinary all-endpoint diagnostic lane with smoke/recovery artifacts. The broader p8/q8 future-work design still refers to future all-endpoint location-scale slope variants, not routine tutorial or coverage-supported routes.

Layer	Fitted q and slope support	Main extractors or diagnostics	Planned or blocked neighbours
Ordinary Gaussian mu	q=1 random intercepts and independent slopes; q=2 intercept-slope correlations; q > 2 numeric mu blocks	summary()$parameters, summary()$covariance, ranef()$terms, corpairs(), profile_targets(), check_drm()	q > 2 correlations are derived-unavailable for direct profile intervals and larger q blocks remain advanced
Ordinary Gaussian sigma	q=1 residual-scale intercepts, independent numeric slopes, and unlabelled correlated intercept-slope and multi-slope blocks on log(sigma)	summary()$parameters, summary()$covariance, profile_targets(), check_drm(), sigma()	labelled residual-scale blocks and cross-formula mu-sigma slope covariance
Random-effect SD surface	sd(group) ~ x_group for unlabelled Gaussian mu random intercepts	predict_parameters(dpar = "sd(group)"), marginal_parameters(), fixed-effect summaries	coefficient-specific sd(group, coef = "x"), spatial/animal/relmat direct-SD siblings, and generic sd*() unification
Ordinary bivariate mu1/mu2	q=2 matching labelled random intercepts, q=2 matching slope-only random-slope blocks, q4/q6 location blocks with smoke artifact routing, and the location endpoints of the first q8 diagnostic lane	corpairs(class = "mean-mean"), summary()$covariance, profile_targets(), check_drm()	broader p8/q8 endpoint variants and predictor-dependent slope corpair() regressions
Ordinary bivariate sigma1/sigma2	q=2 matching labelled random intercepts, slope-only scale-slope blocks, and the scale endpoints of the first q8 diagnostic lane	corpairs(class = "scale-scale"), summary()$covariance, profile_targets()	broader p8/q8 endpoint variants
Same-response mu/sigma	one or more q=2 matching random-intercept blocks, plus matching slope-only blocks within a response	corpairs(class = "mean-scale"), corpairs(class = "mean-scale-slope"), summary()$covariance	cross-response and mismatched-coefficient covariance
All-four ordinary location-scale	constant q=4 random-intercept block across mu1, mu2, sigma1, and sigma2, plus the first q8 all-endpoint diagnostic lane with matching (1 + x | p | id) terms	corpairs() and summary()$covariance report derived latent correlations; Phase 18 q8 recovery artifacts report bias, RMSE, MCSE, and interval unavailability	derived q=4/q8 correlation intervals and broader p8/q8 random-slope endpoint variants
Residual coscale	fixed-effect rho12 ~ ...	rho12(), confint(..., parm = "rho12", newdata = ...), summary()	random effects or structured dependence in rho12
Ordinary corpair() regression	q=2 predictor-dependent group-level correlation for an already fitted block	corpairs(newdata = ...), plot_corpairs()	q=4 correlation regressions and slope-level corpair() regressions
Phylogenetic structure	Gaussian q=1 univariate mu and sigma intercepts with optional matching mu/sigma correlation; one numeric mu slope; the exact q1 sigma one-slope route; Gaussian q=2 bivariate mu1/mu2; Gaussian constant q=4 location-scale intercept block; ordinary Poisson/NB2 q=1 mu intercept-plus-one-slope routes; separate recovery-grade NB2 q1 structured sigma intercept-plus-one-slope	summary()$parameters, marker-specific ranef()$terms, corpairs(level = "phylogenetic") for Gaussian q>=2, profile_targets(), check_drm(); the Gaussian sigma slope is inference-ready with caveats	pure, multiple, or labelled Poisson/NB2 phylogenetic slopes, zero-inflated phylogenetic effects, multiple or labelled Gaussian phylogenetic slopes, phylogenetic slope correlations, direct-SD formulas combined with structured sigma, and structured rho12
Phylogenetic direct SD	sd_phylo(), sd_phylo1(), and sd_phylo2() direct-SD surfaces where documented	fixed-effect summaries, prediction helpers, profile targets where direct	generic sd*() naming across phylo, spatial, animal, and relmat() remains a future unification lane
Coordinate spatial structure	q=1 univariate mu and sigma intercepts with optional matching mu/sigma correlation; one numeric mu slope; a q1 sigma one-slope point-fit/extractor route; q=2 bivariate mu1/mu2 intercept covariance; constant q=4 location-scale intercept block; ordinary Poisson/NB2 q=1 mu intercept-plus-one-slope routes; separate recovery-grade NB2 q1 structured sigma intercept-plus-one-slope; the exact diagnostic-only Poisson zi ~ spatial() intercept; the exact diagnostic-only fixed-zi Poisson mu ~ spatial() intercept; and the exact diagnostic-only fixed-zi NB2 mu ~ spatial() intercept	summary()$parameters, marker-specific ranef()$terms, corpairs(level = "spatial"), summary()$covariance, profile_targets(), check_drm()	the Gaussian spatial sigma-slope interval gate, mesh/SPDE, multiple or labelled Gaussian slopes, slope correlations, direct-SD surfaces, spatial corpair() regression, pure, multiple, or labelled count spatial slopes, and zero-inflated spatial effects outside the exact Poisson zi, fixed-zi Poisson mu, and fixed-zi NB2 mu gates; both fixed-zi routes have no recovery, interval, or coverage promotion
Animal-model structure	q=1 univariate mu and sigma intercepts with optional matching mu/sigma correlation; one numeric mu slope for pedigree, A, or Ainv; the exact A-matrix q1 sigma one-slope route; q=2 bivariate mu1/mu2; constant q=4 location-scale intercept block; ordinary Poisson/NB2 q=1 mu intercept-plus-one-slope routes; separate recovery-grade NB2 q1 structured sigma intercept-plus-one-slope	summary()$parameters, marker-specific ranef()$terms, corpairs(level = "animal"), profile_targets(), check_drm(); the Gaussian sigma slope is inference-ready with caveats	pedigree/Ainv bridge marshalling, sparse large-pedigree construction, multiple or labelled Gaussian slopes, slope correlations, predictor-dependent corpair() regression, direct-SD grammar, pure, multiple, or labelled count animal slopes, and labelled count covariance
relmat() known latent relatedness	q=1 univariate mu and sigma intercepts with optional matching mu/sigma correlation; one numeric mu slope for K or Q; the exact K/Q q1 sigma one-slope route; q=2 bivariate mu1/mu2; constant q=4 location-scale intercept block; ordinary Poisson/NB2 q=1 mu intercept-plus-one-slope routes; separate recovery-grade NB2 q1 structured sigma intercept-plus-one-slope	summary()$parameters, marker-specific ranef()$terms, corpairs(level = "relmat"), profile_targets(), check_drm(); the Gaussian sigma slope is inference-ready with caveats	broader K/Q bridge claims, multiple or labelled Gaussian slopes, slope correlations, predictor-dependent corpair() regression, direct-SD grammar, pure, multiple, or labelled count relmat() slopes, and labelled count covariance
Non-Gaussian ordinary mu	Ordinary mu intercepts/slopes for every fitted univariate family; Poisson/NB2 q1 single-provider structured mu; exact recovery-grade Gamma-phylo, lognormal-phylo/relmat, Gamma-relatedness, Student-spatial, beta-animal, and ordinal-phylo gates; and one crossed NB2 spatial-plus-relatedness route	summary()$parameters, marker-specific ranef()$terms, direct targets from profile_targets(), and check_drm() where exposed; crossed NB2 recovery is design-dependent	correlated/labelled non-Gaussian slopes, pure/multiple structured slopes, simultaneous count types beyond the exact crossed NB2 gate, unsupported inflation/hurdle neighbours, and cross-parameter covariance
Non-Gaussian scale, shape, zero-inflation, and hurdle	fixed-effect formulas where the family supports the component; ordinary NB2, lognormal, and Gamma log-sigma random intercepts; recovery-grade NB2 q=1 structured sigma one-slope slices; one diagnostic-only truncated-NB2 q=1 hu ~ relmat(K/Q) intercept; and exact point-fit-only zero-one-beta zoi and coi random-intercept/same-raw-symbol slope gates	fixed-effect coefficient tables and Wald intervals where implemented; named rows in summary()$parameters and profile_targets(), conditional deviations in ranef()$terms, and check_drm() for the intercept gates; zero-one-beta direct atom-SD targets remain unavailable to profiling; only the exact lognormal and Gamma (M >= 32) ledger domains are inference-ready with caveats	non-Gaussian sigma slopes outside exact ledger gates, structured scale routes outside the NB2 q=1 one-slope gate, random effects in nu, zi, or latent skewness, transformed or mismatched atom slopes, and hu random effects beyond the exact q=1 relmat() intercept

Slope coverage at a glance

Random-effect type	At least one random slope fitted?	Current fitted scope	Not yet fitted
Ordinary Gaussian mu	Yes	independent slopes, one-slope correlated blocks, q > 2 numeric mu blocks	routine high-q teaching and direct q > 2 correlation profiles
Ordinary Gaussian sigma	Yes	independent slopes plus unlabelled correlated intercept-slope and multi-slope blocks	labelled residual-scale and cross-formula mu-sigma slope covariance
Ordinary bivariate Gaussian	Yes	matching slope-only mu1/mu2, same-response mu/sigma, and sigma1/sigma2 q=2 blocks plus q4/q6 location blocks and the first q8 all-endpoint diagnostic lane with smoke/recovery artifact routing	broader p8/q8 all-endpoint variants, q8 coverage or power evidence, and slope-level corpair() regressions
Coordinate spatial	Yes	one univariate Gaussian mu slope plus a q1 sigma one-slope point-fit/extractor route and constant q=4 bivariate Gaussian location-scale intercepts	spatial sigma-slope intervals, multiple or labelled slopes, slope correlations, and non-Gaussian spatial effects outside the exact ordinary Poisson/NB2 q1 spatial mu intercept-plus-one-slope, recovery-grade NB2 q1 spatial sigma, Student-t spatial mu, Poisson spatial zi, fixed-zi Poisson spatial mu, and fixed-zi NB2 spatial mu gates
Phylogenetic	Yes	one univariate Gaussian mu slope plus the exact q1 sigma one-slope route, inference-ready with caveats; exact non-Gaussian gates include ordinary Poisson/NB2 q1 phylogenetic mu intercept-plus-one-slope, recovery-grade NB2 q1 phylogenetic sigma, diagnostic-only Student-t q1 phylogenetic nu, and diagnostic-only cumulative-logit q1 phylogenetic mu	multiple or labelled slopes, slope correlations, direct-SD formulas combined with structured sigma, and non-Gaussian phylogenetic effects outside those exact row-specific gates
Animal-model relatedness	Yes	documented Gaussian routes plus exact ordinary Poisson/NB2 q1 animal mu intercept-plus-one-slope, NB2 q1 animal sigma, and beta animal gates	pedigree/Ainv bridge marshalling, sparse large-pedigree scaling, multiple or labelled slopes, slope correlations, and non-Gaussian animal neighbours outside exact gates
relmat() known latent relatedness	Yes	documented Gaussian routes plus exact ordinary Poisson/NB2 q1 relmat mu intercept-plus-one-slope, NB2 q1 relmat sigma, Gamma q1 relmat mu, and truncated-NB2 q1 relmat hu gates	broader bridge claims, multiple or labelled slopes, slope correlations, direct-SD grammar, and non-Gaussian relmat neighbours outside exact gates
Non-Gaussian ordinary mu	Yes	Ordinary intercepts/slopes for every fitted univariate family; Poisson/NB2 q1 single-provider structured mu; exact non-count gates; one recovery-only crossed NB2 spatial-plus-relatedness mu route	correlated slopes, unsupported inflation/hurdle count-mu effects, pure/multiple/labelled structured slopes, simultaneous structured types beyond the exact crossed NB2 gate, and broader bounded-response dependence
Non-Gaussian scale, shape, zi, hu, ordinal, or bounded-response components	First NB2/lognormal/Gamma scale-intercept slices; exact q1 NB2 structured sigma routes at recovery grade; Poisson zi ~ spatial(), truncated-NB2 hu ~ relmat(K/Q), and cumulative-logit mu ~ phylo() routes are diagnostic-only	fixed effects where implemented; ordinary NB2, lognormal, and Gamma log-sigma random intercepts; exact NB2 phylo()/spatial()/animal()/relmat() structured sigma intercept-plus-one-slope routes; exact diagnostic-only Poisson q1 spatial-zi, truncated-NB2 q1 relatedness-hurdle, and cumulative-logit q1 phylogenetic-mu intercepts	ordinary non-Gaussian scale slopes, richer or labelled structured sigma, structured-sigma intervals/coverage, and random effects for shape, inflation beyond the exact spatial-zi gate, ordinal routes beyond the exact phylogenetic-mu gate, or bounded-response components

Current future-work lanes

The next implementation work should move only one boundary at a time. The detailed slice history lives in the contributor design ledgers. This page keeps only the current user-facing lanes:

Current lane	Why it helps users	Done when
Generic sd*() direct-SD design	Users should not need separate direct-SD names for phylo, spatial, animal, and relmat() routes forever.	The grammar, compatibility route for existing sd_phylo*() helpers, examples, tests, and reference-index plan are explicit before parser work.
Broader p8/q8 location-scale slope planning	Full individual-difference location-scale slope models are scientifically attractive but weakly identified.	The first q8 diagnostic lane stays separate from coverage and power claims, and any broader p8/q8 variant has endpoint classes, parameterization, diagnostics, sample-size gates, and interval policy written before syntax opens.
q=4 interval policy	Users need to know which q=4 rows are point estimates and which have real intervals.	q=4 rows keep derived_interval_unavailable until a validated derived-profile or bootstrap route exists.
Non-Gaussian structured q1 gate	Count users need realistic structural-dependence paths before broad non-Gaussian parity.	Poisson and NB2 q1 phylogenetic mu intercepts are fitted as narrow first slices; broader promotion waits for formal recovery, diagnostics, extractor rows, and interval-status evidence.
Route-specific non-Gaussian issues	Developers need a narrow implementation issue before touching code.	The issue names one family, component, layer, q, comparator, extractor contract, diagnostic contract, interval status, simulation artifact, and user fallback.
Poisson q1 runner contract	The fitted Poisson phylogenetic q1 route needs schema checks before broader simulation claims.	Direct target, extractor, manifest, warning/error, smoke-grid, formal-grid, malformed-neighbour, diagnostic, and artifact tests are specified before the route is promoted beyond smoke evidence.
Map and evidence maintenance	The site should help users fit a supported model rather than read a project diary.	model-map, this article, source-map, the validation-debt register, and stale scans agree after each substantial feature slice.

Common planned requests

Use this table when a desired model is not fitted yet.

If you want…	Fit now	Planned boundary
zero-inflated counts with predictors in the zero process	fixed-effect zi ~ predictors in the supported count family; diagnostic-only Poisson zi ~ spatial(1 | id, coords = coords) q=1 structured intercept	random effects in zi, NB2 zi structure, and Poisson zi structure beyond the first spatial() intercept
hurdle counts with a modelled hurdle probability	fixed-effect hu ~ predictors in hurdle NB2, or one diagnostic-only q=1 hu ~ relmat(1 | id, K/Q = ...) intercept	hu random effects or structured dependence beyond the exact relatedness intercept
phylogenetic or spatial count dependence	ordinary Poisson/NB2 q1 single-provider mu; separate NB2 q1 structured sigma; exact crossed NB2 spatial-plus-relatedness mu when the crossed design identifies both fields	pure, multiple, or labelled structured count slopes, unsupported zero-inflation, richer NB2 structured sigma, simultaneous types beyond the exact crossed gate, and labelled count covariance
full individual-difference location-scale slopes	fitted q2 slope-only mu1/mu2 covariance, smaller univariate pieces, or the first ordinary q8 diagnostic artifact lane when all four endpoints use matching (1 + x | p | id) terms	q8 coverage or power evidence, broader p8/q8 location-scale slope variants, and interval support for derived q8 correlations
structured direct-SD surfaces outside phylogeny	fitted structured intercept/slope SDs and profile_targets() where available	generic spatial, animal, or relmat() direct-SD regression
spatial q4 location-scale covariance	fitted bivariate Gaussian q4 spatial location-scale block when all four endpoints use matching labelled spatial(1 | p | site, coords = coords) terms; treat current q4 evidence as extractor/diagnostic smoke; the separate q1 spatial sigma one-slope route has point-fit/extractor evidence	mesh/SPDE, spatial sigma-slope intervals, multiple or labelled spatial slopes, direct-SD surfaces, predictor-dependent spatial corpair() regression, q4 coverage evidence, and non-Gaussian spatial routes outside the exact ordinary Poisson/NB2 q1 spatial mu intercept-plus-one-slope, recovery-grade NB2 q1 spatial sigma, Student-t spatial mu, Poisson spatial zi, fixed-zi Poisson spatial mu, and fixed-zi NB2 spatial mu gates
NB2 structured count model	single-provider q1 mu intercept-plus-one-slope routes, ordinary NB2 mu, separate recovery-grade q1 structured sigma, or the exact recovery-only crossed spatial-plus-relatedness mu route	pure/multiple/labelled structured mu slopes, unsupported zero-inflated structure, richer structured sigma, simultaneous types beyond the exact crossed gate, and labelled count covariance
Poisson structured count slopes	ordinary Poisson/NB2 q=1 unlabelled phylo()/spatial()/animal()/relmat() intercept-plus-one-slope terms, or independent numeric mu slopes when the grouping is exchangeable	pure, multiple, or labelled structured count slopes need their own recovery and diagnostic evidence
Poisson animal() or relmat() count dependence	ordinary Poisson/NB2 q1 animal/relatedness mu, ordinary count mu, Gaussian animal/relatedness, or the exact crossed NB2 spatial-plus-relatedness mu route	pure/multiple/labelled known-relatedness count slopes, unsupported zero-inflation, and simultaneous types beyond the exact crossed NB2 gate remain planned
non-Gaussian structured scale or shape effects	fixed-effect sigma, nu, zi, or hu formulas where the family supports them; ordinary NB2, lognormal, and Gamma log-sigma random intercepts for plain grouping; separate recovery-grade NB2 q=1 phylo()/spatial()/animal()/relmat() structured sigma intercept-plus-one-slope routes; one diagnostic-only truncated-NB2 q=1 hu ~ relmat(K/Q) intercept	richer or labelled structured scale and shape, zero-inflation, and hurdle random effects beyond the exact relatedness intercept need family-specific likelihood, extractor, diagnostic, and recovery contracts
known sampling covariance plus latent relatedness	Gaussian meta_V(V = V) for known sampling covariance, or Gaussian relmat() for latent relatedness when that is the scientific target	meta_V() is implemented/tested but tier-unregistered, with no interval or coverage claim; non-Gaussian known covariance and latent relatedness should stay separate until each has its own issue and simulation gate
unsupported structured count syntax	fit the nearest fixed-effect or ordinary random-effect model and read check_drm() before interpretation	future error messages should name the unsupported family, component, layer, q, and nearest fitted alternative