predict with pvc not working

[alvinwmtan]

When fitting a gamlss model with pvc(), the predict method doesn't work.

Minimal reprex:

age <- c(17,17,18,18,19,19,17,17,18,18,19,19)
language <- c("eng","eng","eng","eng","eng","eng","spa","spa","spa","spa","spa","spa")
prop <- c(0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.2, 0.3, 0.4, 0.3, 0.6, 0.6)
df <- data.frame(age = age, language = as.factor(language), prop = prop)

mod <- gamlss(prop ~ pvc(age, by = language, lambda=10000), sigma.fo = prop ~ pvc(age, by = language), data = df)

nd <- expand_grid(age = c(17,18,19), language = c("eng", "spa"))
pred <- predict(mod, newdata = nd, type = "response", data = df)
# Error in l$beta : $ operator is invalid for atomic vectors
# In addition: Warning messages:
# 1: In model.matrix.default(~fac - 1, contrast = "") :
#   non-list contrasts argument ignored
# 2: In model.matrix.default(~fac - 1, contrast = "") :
#   non-list contrasts argument ignored
# 3: In model.matrix.default(~fac - 1, contrast = "") :
#   non-list contrasts argument ignored

[TenanATC]

I've also noticed that pvc() appears to throw those warnings when building the model and would be interested to know if they represent an issue that needs resolution.

Though, it is worth noting that the predict() method works fine when the following model is specified:

mod <- gamlss(prop ~ pvc(age, by = language), data = df)

So, it is not entirely clear to me if the issue resides with pvc() exactly or because there is some sparsity or another issue with overall model specification.