The NUTS sampler takes a really long time in this MWE:

```
using Distributions
using Turing
d = Categorical([0.7, 0.29, 0.01])
N = 100
Y = rand(d, N)
@model function test(Y)
p ~ Dirichlet([2,2,2])
for i in 1:N
Y[i] ~ Categorical(p)
end
end
m = test(Y)
chain = sample(m, NUTS(), 1_000)
```

I have thousands of observations for my real problem so I’m going to need to choose a different sampler. I’m hoping someone can provide some suggestions for this kind of problem because I’ve been spoiled by the NUTS sampler just working (for the most part) and not having to tune a different sampler.