I am running a model and would like to fit the zero-inflated component of a ZIP model to a non-linear expression.

The problem is illustrated in the following toy example:

```
train <- data.frame(fread("path/to/data/train.csv"))
counts_formula <- counts ~ L + (c - MaxT) * step(MaxT - c)
zi_formula <- zi ~ K + (d - precip) * step(precip - d)
coef_formula <- L + K + c + d ~ 1
brms_formula <- bf(counts_formula,
zi_formula,
coef_formula,
nl = TRUE)
priors <- c(prior(normal(-10,10), nlpar = "L"),
prior(normal(0,10), nlpar = "K"),
prior(uniform(0.01, 1), nlpar = "c", lb = 0.01, ub = 1),
prior(uniform(0.01, 1), nlpar = "d", lb = 0.01, ub = 1))
fit <- brm(brms_formula,
data = train,
prior = priors,
family = zero_inflated_poisson(),
warmup = 1000, iter = 4000,
chains = 1, cores = 1,
control = list(max_treedepth = 10, adapt_delta = 0.9))
```

This returns the error message:

```
Error: The parameter 'K' is not a valid distributional or non-linear parameter. Did you forget to set 'nl = TRUE'?
Traceback:
1. brm(brms_formula, data = train, prior = priors, family = zero_inflated_poisson(),
. warmup = 50, iter = 200, chains = 1, cores = 1, control = list(max_treedepth = 10,
. adapt_delta = 0.9))
2. brmsterms(formula)
3. brmsterms.brmsformula(formula)
4. stop2("The parameter '", unused_nlpars[1], "' is not a ", "valid distributional or non-linear parameter. ",
. "Did you forget to set 'nl = TRUE'?")
5. stop(..., call. = FALSE)
```

The model runs perfectly well if I set the zero-inflation formula to `zi ~ 1`

, but does not work for `zi ~ K`

with the appropriate priors specified.

OS: Linux

brms version: 2.18.0