Hello! I have been using greta for a few months for a few simple models. However I have been moving to more complicated models to fit, including one that requires integrals. Is there a way to model this with greta? I have tried to use the integrate function however it substitutes the arguments right away (and gives it an error) when I call the function, instead of doing so when I call the mcmc later.

Below I give an example that reproduces the error, where I try to model the integrate of x + a constant:

library(greta)

set.seed(999)

```
# Generate data -----------------------------------------------------------
nobs = 1000
x <- runif(nobs, 0,4)
a <- 2
xb <- c()
integrand <- function(x , c=1){ #function to integrate
return (c-x)
}
for (i in 1:nobs){
xb[i] <- integrate(integrand, lower=0, upper=x[i], c=a)$value
}
y <- rnorm(nobs, xb, sd=0.5)
y <- as_data(y)
x <- as_data(x)
# priors ------------------------------------------------------------------
sigma_y<- cauchy(0,3)
alpha <- variable(dim=1)
mu <- greta_array(dim=nobs)
for(i in nobs){
mu[i] <- integrate(integrand, lower=0, upper=x[i], c=alpha)$value
}
# likelihood --------------------------------------------------------------
distribution(y) <- normal(mu, sigma_y)
```

The error in question:

```
Error in integrate(integrand, lower = 0, upper = x[i], c = alpha) :
non-finite function value
```

I only give the example for the integrate function, but I believe that this might happen with others due to the incompatibility with object types, thus the more generic title.

Thanks in advance!