Hi,

I am trying to fit a simple quantile regression model using BRMS with the asym_laplace distributional family. The command that I am using is as follows:

```
qr.mdl <- brm(bf(lbio.fit ~ s(HadISST.C), quantile = 0.9),
data = dat.fit,
family = asym_laplace())
```

…where I am using a spline as my response curve to describe the 90% percentile.

The model appears to fit ok. However, doing a comparison between the input data and the fitted() values looks like so:

Straight away this doesn’t seem to look like 10% of the points are above the line. Checking this confirms it - 65% of the observations are above the line (rather than the 10% I expect). Binning the x-axis and looking at it in chunks gives similar results.

So, my question is, what is going wrong? Have I misconfigured (or misunderstood) my model specification? Or is there something I am missing?

Best wishes,

Mark

- Operating System: Manjaro Linux
- brms Version: 2.80