One-inflated binomial for proportions with excess ones (100% success). Useful when perfect detection/success has a structural component.
$$P(Y = n) = \psi + (1 - \psi) \cdot p^n$$ $$P(Y = y) = (1 - \psi) \cdot \binom{n}{y} p^y (1-p)^{n-y}, \quad y < n$$
Details
Use this when excess 100% success rates occur due to:
Perfect detection in highly suitable habitat
Saturation effects
Structural constraints ensuring full success
Examples
# Create family object
fam <- ratiod_oibinomial()
print(fam)
#> tulpaRatio family: oibinomial
#> [Zero-inflated model]
#> One-inflated binomial numerator, fixed trials denominator
#>
#> Numerator: binomial(logit)
#> ZI prob: bernoulli()
#> Denominator: fixed (fixed)