Hi all,

Is this expected that calling Cholesky_decompose with a non positive definite matrix in transformed parameter block would NOT cause error (but divergent transitions) while doing the same in generated quantities would cause error to be reported?

```
data {
int N;
}
parameters {
corr_matrix[N] Sigma;
real x;
}
/*
transformed parameters {
matrix[N,N] L_Sigma;
{
matrix[N,N] tmp;
tmp = Sigma;
tmp[1,2] = x;
tmp[2,1] = x;
L_Sigma = cholesky_decompose(tmp);
}
}
*/
model {
x ~ normal (0,1);
}
generated quantities {
matrix[N,N] L_Sigma;
{
matrix[N,N] tmp;
tmp = Sigma;
tmp[1,2] = x;
tmp[2,1] = x;
L_Sigma = cholesky_decompose(tmp);
}
}
```

in transformed parameter block:

```
> sampling (t807, chains=1, data=list(N=2, Sigma = matrix(c(1,1,2,1), nrow=2)))
SAMPLING FOR MODEL 't807' NOW (CHAIN 1).
Chain 1:
Chain 1: Gradient evaluation took 1.7e-05 seconds
Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 0.17 seconds.
Chain 1: Adjust your expectations accordingly!
Chain 1:
Chain 1:
Chain 1: Iteration: 1 / 2000 [ 0%] (Warmup)
Chain 1: Iteration: 200 / 2000 [ 10%] (Warmup)
Chain 1: Iteration: 400 / 2000 [ 20%] (Warmup)
Chain 1: Iteration: 600 / 2000 [ 30%] (Warmup)
Chain 1: Iteration: 800 / 2000 [ 40%] (Warmup)
Chain 1: Iteration: 1000 / 2000 [ 50%] (Warmup)
Chain 1: Iteration: 1001 / 2000 [ 50%] (Sampling)
Chain 1: Iteration: 1200 / 2000 [ 60%] (Sampling)
Chain 1: Iteration: 1400 / 2000 [ 70%] (Sampling)
Chain 1: Iteration: 1600 / 2000 [ 80%] (Sampling)
Chain 1: Iteration: 1800 / 2000 [ 90%] (Sampling)
Chain 1: Iteration: 2000 / 2000 [100%] (Sampling)
Chain 1:
Chain 1: Elapsed Time: 0.08869 seconds (Warm-up)
Chain 1: 0.073575 seconds (Sampling)
Chain 1: 0.162265 seconds (Total)
Chain 1:
Inference for Stan model: t807.
1 chains, each with iter=2000; warmup=1000; thin=1;
post-warmup draws per chain=1000, total post-warmup draws=1000.
mean se_mean sd 2.5% 25% 50% 75% 97.5% n_eff Rhat
Sigma[1,1] 1.00 NaN 0.00 1.00 1.00 1.00 1.00 1.00 NaN NaN
Sigma[1,2] -0.01 0.03 0.58 -0.94 -0.51 -0.04 0.48 0.96 369 1
Sigma[2,1] -0.01 0.03 0.58 -0.94 -0.51 -0.04 0.48 0.96 369 1
Sigma[2,2] 1.00 0.00 0.00 1.00 1.00 1.00 1.00 1.00 839 1
x 0.07 0.03 0.56 -0.91 -0.40 0.09 0.55 0.95 264 1
L_Sigma[1,1] 1.00 NaN 0.00 1.00 1.00 1.00 1.00 1.00 NaN NaN
L_Sigma[1,2] 0.00 NaN 0.00 0.00 0.00 0.00 0.00 0.00 NaN NaN
L_Sigma[2,1] 0.07 0.03 0.56 -0.91 -0.40 0.09 0.55 0.95 264 1
L_Sigma[2,2] 0.80 0.01 0.22 0.19 0.69 0.88 0.97 1.00 334 1
lp__ -0.77 0.06 0.90 -2.86 -0.96 -0.49 -0.23 -0.03 195 1
Samples were drawn using NUTS(diag_e) at Wed Nov 28 17:27:36 2018.
For each parameter, n_eff is a crude measure of effective sample size,
and Rhat is the potential scale reduction factor on split chains (at
convergence, Rhat=1).
Warning messages:
1: There were 435 divergent transitions after warmup. Increasing adapt_delta above 0.8 may help. See
http://mc-stan.org/misc/warnings.html#divergent-transitions-after-warmup
2: Examine the pairs() plot to diagnose sampling problems
```

In generated quantities block

```
<- stan_model ("t807.stan")
hash mismatch so recompiling; make sure Stan code ends with a blank line
During startup - Warning message:
Setting LC_CTYPE failed, using "C"
> sampling (t807, chains=1, data=list(N=2, Sigma = matrix(c(1,1,2,1), nrow=2)))
SAMPLING FOR MODEL 't807' NOW (CHAIN 1).
Chain 1:
Chain 1: Gradient evaluation took 1.2e-05 seconds
Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 0.12 seconds.
Chain 1: Adjust your expectations accordingly!
Chain 1:
Chain 1:
Chain 1: Iteration: 1 / 2000 [ 0%] (Warmup)
Chain 1: Exception: cholesky_decompose: Matrix m is not positive definite (in 'model18322d1bb4ec_t807' at line 42)
Chain 1: Exception: cholesky_decompose: Matrix m is not positive definite (in 'model18322d1bb4ec_t807' at line 42)
Chain 1: Exception: cholesky_decompose: Matrix m is not positive definite (in 'model18322d1bb4ec_t807' at line 42)
Chain 1: Exception: cholesky_decompose: Matrix m is not positive definite (in 'model18322d1bb4ec_t807' at line 42)
...
...
Chain 1: Iteration: 2000 / 2000 [100%] (Sampling)
Chain 1:
Chain 1: Elapsed Time: 0.027963 seconds (Warm-up)
Chain 1: 0.024731 seconds (Sampling)
Chain 1: 0.052694 seconds (Total)
Chain 1:
[1] "Error in sampler$call_sampler(args_list[[i]]) : "
[2] " Exception: cholesky_decompose: Matrix m is not positive definite (in 'model18322d1bb4ec_t807' at line 42)"
error occurred during calling the sampler; sampling not done
```