sapsi
#1
Let me explain. Suppose i have a model with

```
y ~ s(time,k=4)
```

where `time = 1 ... N`

and i want the spline to be insenstive to changes in `y`

when `time \in [N-14,N]`

(here `N`

is ~700).

One thing i’ve been doing is placing tight priors (to reduce the prior sigma for the spline)

```
prior = c( set_prior("exponential(8)", class = "sds",coef="s(i,k=4)"))
```

but how can i allow it be ‘freer’ for `time<(N-14)`

but very insensitive for `N >= time >=(N-14)`

It sounds like you want a restricted cubic spline. If you search for `rcs`

on Discourse a few threads will come up about how to do that.

sapsi
#3
Thanks for the suggestion. Will look into it

There are splines where you can specify linear effects at the end, or constant effect.

You could set the time N >= time >=(N-14) to time - 14.

You may also get some ideas from wavelet implementations depending on your signal.

https://www.mathworks.com/help/wavelet/ug/dealing-with-border-distortion.html

sapsi
#5
Sorry for the late reply. Yes this is very nice idea.