I was delighted to see that brms allows shape constrained smooths as from the scam package as part of its formula syntax. However, the post-processing such as marginal_effects() does not seem to work. I found this old post by Paul https://groups.google.com/d/msg/brms-users/hYF6jVEvOvU/EKT6qaP_AwAJ, but even if I follow those steps and load the script (available at the link above), I do get the same error message. I’d appreciate any pointers you might have.

```
library(scam)
Predict.matrix.mpi.smooth<-function(object,data)
## prediction method function for the `mpi' smooth class
{ m <- object$m+1; # spline order, m+1=3 default for cubic spline
q <- object$df ## +1
Sig <- matrix(0,q,q) # Define Matrix Sigma
# elements of matrix Sigma for increasing smooth
for (i in 1:q) Sig[i,1:i] <- 1
## find spline basis inner knot range...
ll <- object$knots[m+1];ul <- object$knots[length(object$knots)-m]
m <- m + 1
x <- data[[object$term]]
n <- length(x)
ind <- x<=ul & x>=ll ## data in range
if (sum(ind)==n) { ## all in range
X <- splines::spline.des(object$knots,x,m)$design
X <- X[,2:(q+1)]%*%Sig ## X <- X%*%Sig
} else { ## some extrapolation needed
## matrix mapping coefs to value and slope at end points...
D <- splines::spline.des(object$knots,c(ll,ll,ul,ul),m,c(0,1,0,1))$design
X <- matrix(0,n,ncol(D)) ## full predict matrix
if (sum(ind)> 0) X[ind,] <- splines::spline.des(object$knots,x[ind],m)$design ## interior rows
## Now add rows for linear extrapolation...
ind <- x < ll
if (sum(ind)>0) X[ind,] <- cbind(1,x[ind]-ll)%*%D[1:2,]
ind <- x > ul
if (sum(ind)>0) X[ind,] <- cbind(1,x[ind]-ul)%*%D[3:4,]
X <- X[,2:(q+1)]%*%Sig
}
X
}
library(brms)
b = brm(time ~ s(age, bs = "mpi"),
data = kidney)
marginal_effects(b)
# yields: Error in X %*% re$trans.U : non-conformable arguments
> version
_
platform x86_64-apple-darwin15.6.0
arch x86_64
os darwin15.6.0
system x86_64, darwin15.6.0
status
major 3
minor 5.1
year 2018
month 07
day 02
svn rev 74947
language R
version.string R version 3.5.1 (2018-07-02)
nickname Feather Spray
```