I’m trying to understand what is plotted in the violin based on `yrep`

.

Say that my data looks like this:

```
data <- data.frame(n= 1:50, group= rep(1:10,5), x=rnorm(50), y= rnorm(50))
```

I fit a linear model, and I get my `y_rep`

. When I use `ppc_dens_overlay`

I get one density plot for each simulated dataset, so if my data has 50 observation and I have 20 draws from the posterior predictive distribution. I will get 20 light blue density plots made by 50 observations each, right? This makes total sense to me.

I want to have different plots for each group, I was expecting to find a `ppc_dens_overlay_grouped`

where each group appears in one facet, and so on each facet I will still have 20 light blue density plots but based on 5 observations each. As you know, there is no function like that and the closest thing is `ppc_violin_grouped`

.

```
ppc_violin_grouped(y, yrep, group= data$group)
```

What I don’t understand is how come `ppc_violin_grouped`

gives me **one** “predicted” violin for each group without choosing any stats. Is it just making each violin out of the 20 (draws) * 5 (observations for group) y_rep ignoring from which draw each y_rep is coming? If so, does it make sense? Shouldn’t I get 20 violin overlayed for each group?

I hope my problem is clear, if not I’ll be happy to expand and give more examples.