I have a straightforward Ordered Logistic model coded as:

```
data {
int<lower = 2> K;
int<lower = 0> N;
int<lower = 1> D;
int<lower = 1, upper = K> y[N];
row_vector[D] x[N];
}
parameters {
vector[D] beta;
ordered[K - 1] c;
}
model {
beta ~ std_normal();
for (n in 1:N) {
y[n] ~ ordered_logistic(x[n] * beta, c);
}
}
```

with N \approx~100, D \approx 30. I would like to use Projective Variable Selection as in Piironen et al., using the package `projpred`

.

Sadly, the ordered logistic model has not a reference model implemented (`no applicable method for 'get_refmodel' applied to an object of class "stanfit"`

). Any advice on how to implement variable selection for an OL model?