Hi Stan/rstanarm Users,

I am new to the overall Stan environment and still trying to learn it’s many subtleties. One simple problem I am trying to solve is normal linear regression where I have a known diagonal covariance matrix that isn’t the identity matrix. Using the standard `LM`

template, this would be

```
model.lm <- lm(formula = Y ~ X, data=d, weights=W)
```

where the weights `W`

are the precision estimates of the dependent variable `Y`

at each `X`

point. Since the syntax is very similar, the R code below was my guess as to what it should be in rstanarm.

```
model.rstanarm <- stan_glm(
formula = Y ~ X, data=d, weights=W,
family = gaussian(),
prior=priors.slope, prior_intercept=priors.int
)
```

Is this correct or should I be using the `prior.aux`

variable in `stan_glm()`

to specify my knowledge about the covariance matrix rather than weights?