nbinom2() defines a one-response count distribution with formulas for the
mean mu and overdispersion scale sigma.
Details
The implemented contract is
log(mu) = eta_mu, log(sigma) = eta_sigma, and
Var(y) = mu + sigma^2 * mu^2. Thus larger sigma means greater
extra-Poisson variation. Internally this is equivalent to the usual NB2
size parameter size = 1 / sigma^2. Ordinary non-zero-inflated NB2 models
also support first-slice random intercepts on the log-sigma predictor,
such as bf(count ~ x, sigma ~ z + (1 | id)). Structured sigma effects
(phylo/spatial/animal/relmat) also fit as a point-recovery route
(trust the point estimate, not the interval; not yet coverage-verified).
NB2 sigma random slopes and zero-inflated NB2 sigma random effects
remain planned.